id
stringlengths
9
10
submitter
stringlengths
1
64
authors
stringlengths
4
20.7k
title
stringlengths
4
246
comments
stringlengths
1
523
journal-ref
stringlengths
4
404
doi
stringlengths
11
153
report-no
stringlengths
2
254
categories
stringlengths
5
98
license
stringclasses
9 values
orig_abstract
stringlengths
14
3.35k
versions
listlengths
1
60
update_date
stringlengths
10
10
authors_parsed
listlengths
1
1.35k
abstract
stringlengths
11
3.34k
1709.00273
Haitian Pang
Haitian Pang, Lin Gao, Qinghua Ding and Lifeng Sun
When Data Sponsoring Meets Edge Caching: A Game-Theoretic Analysis
6 pages, accepted by GLOBECOM 2017
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data sponsoring is a widely-used incentive method in today's cellular networks, where video content providers (CPs) cover part or all of the cellular data cost for mobile users so as to attract more video users and increase data traffic. In the forthcoming 5G cellular networks, edge caching is emerging as a promising...
[ { "created": "Fri, 1 Sep 2017 12:28:06 GMT", "version": "v1" } ]
2017-09-04
[ [ "Pang", "Haitian", "" ], [ "Gao", "Lin", "" ], [ "Ding", "Qinghua", "" ], [ "Sun", "Lifeng", "" ] ]
Data sponsoring is a widely-used incentive method in today's cellular networks, where video content providers (CPs) cover part or all of the cellular data cost for mobile users so as to attract more video users and increase data traffic. In the forthcoming 5G cellular networks, edge caching is emerging as a promising t...
2408.01526
Lukas Kratochvila
Lukas Kratochvila, Gijs de Jong, Monique Arkesteijn, Simon Bilik, Tomas Zemcik, Karel Horak, Jan S. Rellermeyer
Multi-Unit Floor Plan Recognition and Reconstruction Using Improved Semantic Segmentation of Raster-Wise Floor Plans
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Digital twins have a major potential to form a significant part of urban management in emergency planning, as they allow more efficient designing of the escape routes, better orientation in exceptional situations, and faster rescue intervention. Nevertheless, creating the twins still remains a largely manual effort, ...
[ { "created": "Fri, 2 Aug 2024 18:36:45 GMT", "version": "v1" } ]
2024-08-06
[ [ "Kratochvila", "Lukas", "" ], [ "de Jong", "Gijs", "" ], [ "Arkesteijn", "Monique", "" ], [ "Bilik", "Simon", "" ], [ "Zemcik", "Tomas", "" ], [ "Horak", "Karel", "" ], [ "Rellermeyer", "Jan S.", "" ] ]
Digital twins have a major potential to form a significant part of urban management in emergency planning, as they allow more efficient designing of the escape routes, better orientation in exceptional situations, and faster rescue intervention. Nevertheless, creating the twins still remains a largely manual effort, du...
2204.02929
Carlos Linares L\'opez
Sofia Lemons and Carlos Linares L\'opez and Robert C. Holte and Wheeler Ruml
Beam Search: Faster and Monotonic
9 pages, 15 figures, 3 algorithms, published in the International Conference on Automated Planning and Scheduling ICAPS 2022
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Beam search is a popular satisficing approach to heuristic search problems that allows one to trade increased computation time for lower solution cost by increasing the beam width parameter. We make two contributions to the study of beam search. First, we show how to make beam search monotonic; that is, we provide a ...
[ { "created": "Wed, 6 Apr 2022 16:40:13 GMT", "version": "v1" } ]
2022-04-07
[ [ "Lemons", "Sofia", "" ], [ "López", "Carlos Linares", "" ], [ "Holte", "Robert C.", "" ], [ "Ruml", "Wheeler", "" ] ]
Beam search is a popular satisficing approach to heuristic search problems that allows one to trade increased computation time for lower solution cost by increasing the beam width parameter. We make two contributions to the study of beam search. First, we show how to make beam search monotonic; that is, we provide a ne...
2402.06852
Di Zhang
Di Zhang, Wei Liu, Qian Tan, Jingdan Chen, Hang Yan, Yuliang Yan, Jiatong Li, Weiran Huang, Xiangyu Yue, Wanli Ouyang, Dongzhan Zhou, Shufei Zhang, Mao Su, Han-Sen Zhong and Yuqiang Li
ChemLLM: A Chemical Large Language Model
9 pages, 5 figures
null
null
null
cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
Large language models (LLMs) have made impressive progress in chemistry applications. However, the community lacks an LLM specifically designed for chemistry. The main challenges are two-fold: firstly, most chemical data and scientific knowledge are stored in structured databases, which limits the model's ability to ...
[ { "created": "Sat, 10 Feb 2024 01:11:59 GMT", "version": "v1" }, { "created": "Thu, 25 Apr 2024 14:34:28 GMT", "version": "v2" } ]
2024-04-26
[ [ "Zhang", "Di", "" ], [ "Liu", "Wei", "" ], [ "Tan", "Qian", "" ], [ "Chen", "Jingdan", "" ], [ "Yan", "Hang", "" ], [ "Yan", "Yuliang", "" ], [ "Li", "Jiatong", "" ], [ "Huang", "Weiran", ""...
Large language models (LLMs) have made impressive progress in chemistry applications. However, the community lacks an LLM specifically designed for chemistry. The main challenges are two-fold: firstly, most chemical data and scientific knowledge are stored in structured databases, which limits the model's ability to su...
2311.13286
Michael Klenk
Michael Klenk
Algorithmic Transparency and Manipulation
null
null
10.1007/s13347-023-00678-9
null
cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
A series of recent papers raises worries about the manipulative potential of algorithmic transparency. But while the concern is apt and relevant, it is based on a fraught understanding of manipulation. Therefore, this paper draws attention to the indifference view of manipulation, which explains better than the vulne...
[ { "created": "Wed, 22 Nov 2023 10:09:06 GMT", "version": "v1" } ]
2023-11-23
[ [ "Klenk", "Michael", "" ] ]
A series of recent papers raises worries about the manipulative potential of algorithmic transparency. But while the concern is apt and relevant, it is based on a fraught understanding of manipulation. Therefore, this paper draws attention to the indifference view of manipulation, which explains better than the vulnera...
2404.03591
Orcun Yildiz
Orcun Yildiz, Dmitriy Morozov, Arnur Nigmetov, Bogdan Nicolae, and Tom Peterka
Wilkins: HPC In Situ Workflows Made Easy
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however, face challenges in handling the growing complexity and diverse computational requirements of scientific tasks. In this work, we present Wi...
[ { "created": "Thu, 4 Apr 2024 16:59:13 GMT", "version": "v1" } ]
2024-04-05
[ [ "Yildiz", "Orcun", "" ], [ "Morozov", "Dmitriy", "" ], [ "Nigmetov", "Arnur", "" ], [ "Nicolae", "Bogdan", "" ], [ "Peterka", "Tom", "" ] ]
In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however, face challenges in handling the growing complexity and diverse computational requirements of scientific tasks. In this work, we present Wilk...
2310.14444
Asif Imran
Asif Imran and Tevfik Kosar
URegM: a unified prediction model of resource consumption for refactoring software smells in open source cloud
null
2022 The 3rd European Symposium on Software Engineering (ESSE 2022)
null
null
cs.SE cs.LG
http://creativecommons.org/licenses/by/4.0/
The low cost and rapid provisioning capabilities have made the cloud a desirable platform to launch complex scientific applications. However, resource utilization optimization is a significant challenge for cloud service providers, since the earlier focus is provided on optimizing resources for the applications that ...
[ { "created": "Sun, 22 Oct 2023 23:03:35 GMT", "version": "v1" } ]
2023-10-24
[ [ "Imran", "Asif", "" ], [ "Kosar", "Tevfik", "" ] ]
The low cost and rapid provisioning capabilities have made the cloud a desirable platform to launch complex scientific applications. However, resource utilization optimization is a significant challenge for cloud service providers, since the earlier focus is provided on optimizing resources for the applications that ru...
1708.01938
Ori Ganoni
Ori Ganoni, Ramakrishnan Mukundan
A Framework for Visually Realistic Multi-robot Simulation in Natural Environment
WSCG 2017 conference
null
null
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a generalized framework for the simulation of multiple robots and drones in highly realistic models of natural environments. The proposed simulation architecture uses the Unreal Engine4 for generating both optical and depth sensor outputs from any position and orientation within the environment an...
[ { "created": "Sun, 6 Aug 2017 21:41:42 GMT", "version": "v1" } ]
2017-08-08
[ [ "Ganoni", "Ori", "" ], [ "Mukundan", "Ramakrishnan", "" ] ]
This paper presents a generalized framework for the simulation of multiple robots and drones in highly realistic models of natural environments. The proposed simulation architecture uses the Unreal Engine4 for generating both optical and depth sensor outputs from any position and orientation within the environment and ...
2012.08777
Mariya Hendriksen
Mariya Hendriksen, Ernst Kuiper, Pim Nauts, Sebastian Schelter, Maarten de Rijke
Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers
10 pages, accepted at SIGIR eCommerce 2020
null
null
null
cs.IR
http://creativecommons.org/licenses/by/4.0/
The popularity of e-commerce platforms continues to grow. Being able to understand, and predict customer behavior is essential for customizing the user experience through personalized result presentations, recommendations, and special offers. Previous work has considered a broad range of prediction models as well as ...
[ { "created": "Wed, 16 Dec 2020 07:43:44 GMT", "version": "v1" } ]
2020-12-17
[ [ "Hendriksen", "Mariya", "" ], [ "Kuiper", "Ernst", "" ], [ "Nauts", "Pim", "" ], [ "Schelter", "Sebastian", "" ], [ "de Rijke", "Maarten", "" ] ]
The popularity of e-commerce platforms continues to grow. Being able to understand, and predict customer behavior is essential for customizing the user experience through personalized result presentations, recommendations, and special offers. Previous work has considered a broad range of prediction models as well as fe...
2208.12389
Christian Manasseh
Christian Manasseh, Razvan Veliche, Jared Bennett, Hamilton Clouse
Static Seeding and Clustering of LSTM Embeddings to Learn from Loosely Time-Decoupled Events
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Humans learn from the occurrence of events in a different place and time to predict similar trajectories of events. We define Loosely Decoupled Timeseries (LDT) phenomena as two or more events that could happen in different places and across different timelines but share similarities in the nature of the event and th...
[ { "created": "Fri, 26 Aug 2022 01:00:19 GMT", "version": "v1" } ]
2022-08-29
[ [ "Manasseh", "Christian", "" ], [ "Veliche", "Razvan", "" ], [ "Bennett", "Jared", "" ], [ "Clouse", "Hamilton", "" ] ]
Humans learn from the occurrence of events in a different place and time to predict similar trajectories of events. We define Loosely Decoupled Timeseries (LDT) phenomena as two or more events that could happen in different places and across different timelines but share similarities in the nature of the event and the ...
1812.01077
Carlos Sarraute
Carlos Sarraute, Martin Minnoni
Brief survey of Mobility Analyses based on Mobile Phone Datasets
Workshop on Urban Computing and Society. Petropolis, RJ, Brazil. Nov 28, 2018
null
null
null
cs.SI cs.CY cs.LG stat.ML
http://creativecommons.org/licenses/by-nc-sa/4.0/
This is a brief survey of the research performed by Grandata Labs in collaboration with numerous academic groups around the world on the topic of human mobility. A driving theme in these projects is to use and improve Data Science techniques to understand mobility, as it can be observed through the lens of mobile pho...
[ { "created": "Mon, 3 Dec 2018 20:46:27 GMT", "version": "v1" } ]
2020-02-27
[ [ "Sarraute", "Carlos", "" ], [ "Minnoni", "Martin", "" ] ]
This is a brief survey of the research performed by Grandata Labs in collaboration with numerous academic groups around the world on the topic of human mobility. A driving theme in these projects is to use and improve Data Science techniques to understand mobility, as it can be observed through the lens of mobile phone...
2110.14890
Hongyu Ren
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
null
null
null
null
cs.LG cs.AI cs.DB cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge graphs (KGs) capture knowledge in the form of head--relation--tail triples and are a crucial component in many AI systems. There are two important reasoning tasks on KGs: (1) single-hop knowledge graph completion, which involves predicting individual links in the KG; and (2), multi-hop reasoning, where the ...
[ { "created": "Thu, 28 Oct 2021 05:02:33 GMT", "version": "v1" }, { "created": "Mon, 1 Nov 2021 22:50:51 GMT", "version": "v2" } ]
2021-11-03
[ [ "Ren", "Hongyu", "" ], [ "Dai", "Hanjun", "" ], [ "Dai", "Bo", "" ], [ "Chen", "Xinyun", "" ], [ "Zhou", "Denny", "" ], [ "Leskovec", "Jure", "" ], [ "Schuurmans", "Dale", "" ] ]
Knowledge graphs (KGs) capture knowledge in the form of head--relation--tail triples and are a crucial component in many AI systems. There are two important reasoning tasks on KGs: (1) single-hop knowledge graph completion, which involves predicting individual links in the KG; and (2), multi-hop reasoning, where the go...
2012.10431
Elias Gr\"unewald
Elias Gr\"unewald and Frank Pallas
TILT: A GDPR-Aligned Transparency Information Language and Toolkit for Practical Privacy Engineering
Accepted for publication at the ACM Conference on Fairness, Accountability, and Transparency 2021 (ACM FAccT'21). This is a preprint manuscript (authors' own version before final copy-editing)
null
10.1145/3442188.3445925
null
cs.CY cs.CR cs.FL cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present TILT, a transparency information language and toolkit explicitly designed to represent and process transparency information in line with the requirements of the GDPR and allowing for a more automated and adaptive use of such information than established, legalese data protection policies do....
[ { "created": "Fri, 18 Dec 2020 18:45:04 GMT", "version": "v1" } ]
2022-09-26
[ [ "Grünewald", "Elias", "" ], [ "Pallas", "Frank", "" ] ]
In this paper, we present TILT, a transparency information language and toolkit explicitly designed to represent and process transparency information in line with the requirements of the GDPR and allowing for a more automated and adaptive use of such information than established, legalese data protection policies do. W...
2406.05388
Giuliano Cornacchia
Giuliano Cornacchia, Ludovico Lemma, Luca Pappalardo
Popularity-based Alternative Routing
null
null
null
null
cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Alternative routing is crucial to minimize the environmental impact of urban transportation while enhancing road network efficiency and reducing traffic congestion. Existing methods neglect information about road popularity, possibly leading to unintended consequences such as increasing emissions and congestion. This...
[ { "created": "Sat, 8 Jun 2024 07:45:56 GMT", "version": "v1" } ]
2024-06-11
[ [ "Cornacchia", "Giuliano", "" ], [ "Lemma", "Ludovico", "" ], [ "Pappalardo", "Luca", "" ] ]
Alternative routing is crucial to minimize the environmental impact of urban transportation while enhancing road network efficiency and reducing traffic congestion. Existing methods neglect information about road popularity, possibly leading to unintended consequences such as increasing emissions and congestion. This p...
2305.17764
Yaron Shany
Amit Berman, Yaron Shany, and Itzhak Tamo
Efficient Algorithms for Constructing Minimum-Weight Codewords in Some Extended Binary BCH Codes
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present $O(m^3)$ algorithms for specifying the support of minimum-weight words of extended binary BCH codes of length $n=2^m$ and designed distance $d(m,s,i):=2^{m-1-s}-2^{m-1-i-s}$ for some values of $m,i,s$, where $m$ may grow to infinity. The support is specified as the sum of two sets: a set of $2^{2i-1}-2^{i-...
[ { "created": "Sun, 28 May 2023 16:22:58 GMT", "version": "v1" } ]
2023-05-30
[ [ "Berman", "Amit", "" ], [ "Shany", "Yaron", "" ], [ "Tamo", "Itzhak", "" ] ]
We present $O(m^3)$ algorithms for specifying the support of minimum-weight words of extended binary BCH codes of length $n=2^m$ and designed distance $d(m,s,i):=2^{m-1-s}-2^{m-1-i-s}$ for some values of $m,i,s$, where $m$ may grow to infinity. The support is specified as the sum of two sets: a set of $2^{2i-1}-2^{i-1}...
2106.11021
Marc Canellas
Marc Canellas
Defending IEEE Software Standards in Federal Criminal Court
13 pages, 0 figures, 1 table
Computer, vol. 54, no. 6, pp. 14--23, Jun. 2021
10.1109/MC.2020.3038630
null
cs.CY
http://creativecommons.org/licenses/by-nc-nd/4.0/
IEEE's 1012 Standard for independent software and hardware verification and validation (IV&V) is under attack in U.S. federal criminal court. As software spreads through the criminal legal system, scientists, engineers, and IEEE have an essential role in ensuring courts understand and respect IEEE 1012 and IV&V. If s...
[ { "created": "Thu, 10 Jun 2021 02:40:01 GMT", "version": "v1" } ]
2021-06-22
[ [ "Canellas", "Marc", "" ] ]
IEEE's 1012 Standard for independent software and hardware verification and validation (IV&V) is under attack in U.S. federal criminal court. As software spreads through the criminal legal system, scientists, engineers, and IEEE have an essential role in ensuring courts understand and respect IEEE 1012 and IV&V. If sci...
1905.04660
Prasad Raghavendra
Prasad Raghavendra and Morris Yau
List Decodable Learning via Sum of Squares
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the list-decodable learning setup, an overwhelming majority (say a $1-\beta$-fraction) of the input data consists of outliers and the goal of an algorithm is to output a small list $\mathcal{L}$ of hypotheses such that one of them agrees with inliers. We develop a framework for list-decodable learning via the Sum-...
[ { "created": "Sun, 12 May 2019 07:27:53 GMT", "version": "v1" } ]
2019-05-14
[ [ "Raghavendra", "Prasad", "" ], [ "Yau", "Morris", "" ] ]
In the list-decodable learning setup, an overwhelming majority (say a $1-\beta$-fraction) of the input data consists of outliers and the goal of an algorithm is to output a small list $\mathcal{L}$ of hypotheses such that one of them agrees with inliers. We develop a framework for list-decodable learning via the Sum-of...
2210.11471
Hadas Orgad
Hadas Orgad and Yonatan Belinkov
Choose Your Lenses: Flaws in Gender Bias Evaluation
Accepted to the 4th Workshop on Gender Bias in Natural Language Processing
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Considerable efforts to measure and mitigate gender bias in recent years have led to the introduction of an abundance of tasks, datasets, and metrics used in this vein. In this position paper, we assess the current paradigm of gender bias evaluation and identify several flaws in it. First, we highlight the importance...
[ { "created": "Thu, 20 Oct 2022 17:59:55 GMT", "version": "v1" } ]
2022-10-21
[ [ "Orgad", "Hadas", "" ], [ "Belinkov", "Yonatan", "" ] ]
Considerable efforts to measure and mitigate gender bias in recent years have led to the introduction of an abundance of tasks, datasets, and metrics used in this vein. In this position paper, we assess the current paradigm of gender bias evaluation and identify several flaws in it. First, we highlight the importance o...
1802.09292
Krishna Murthy Jatavallabhula
Parv Parkhiya, Rishabh Khawad, J. Krishna Murthy, Brojeshwar Bhowmick, K. Madhava Krishna
Constructing Category-Specific Models for Monocular Object-SLAM
Accepted to ICRA 2018
null
null
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new paradigm for real-time object-oriented SLAM with a monocular camera. Contrary to previous approaches, that rely on object-level models, we construct category-level models from CAD collections which are now widely available. To alleviate the need for huge amounts of labeled data, we develop a renderin...
[ { "created": "Mon, 26 Feb 2018 13:42:40 GMT", "version": "v1" } ]
2018-02-27
[ [ "Parkhiya", "Parv", "" ], [ "Khawad", "Rishabh", "" ], [ "Murthy", "J. Krishna", "" ], [ "Bhowmick", "Brojeshwar", "" ], [ "Krishna", "K. Madhava", "" ] ]
We present a new paradigm for real-time object-oriented SLAM with a monocular camera. Contrary to previous approaches, that rely on object-level models, we construct category-level models from CAD collections which are now widely available. To alleviate the need for huge amounts of labeled data, we develop a rendering ...
2103.09764
Yanlun Tu
Yanlun Tu, Houchao Lei, Wei Long, Yang Yang
HAMIL: Hierarchical Aggregation-Based Multi-Instance Learning for Microscopy Image Classification
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-instance learning is common for computer vision tasks, especially in biomedical image processing. Traditional methods for multi-instance learning focus on designing feature aggregation methods and multi-instance classifiers, where the aggregation operation is performed either in feature extraction or learning p...
[ { "created": "Wed, 17 Mar 2021 16:34:08 GMT", "version": "v1" } ]
2021-03-18
[ [ "Tu", "Yanlun", "" ], [ "Lei", "Houchao", "" ], [ "Long", "Wei", "" ], [ "Yang", "Yang", "" ] ]
Multi-instance learning is common for computer vision tasks, especially in biomedical image processing. Traditional methods for multi-instance learning focus on designing feature aggregation methods and multi-instance classifiers, where the aggregation operation is performed either in feature extraction or learning pha...
1808.06893
Desislava Dimitrova
Desislava Dimitrova, John Liagouris, Sebastian Wicki, Moritz Hoffmann, Vasiliki Kalavri, Timothy Roscoe
DeltaPath: dataflow-based high-performance incremental routing
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Routing controllers must react quickly to failures, reconfigurations and workload or policy changes, to ensure service performance and cost-efficient network operation. We propose a general execution model which views routing as an incremental data-parallel computation on a graph-based network model plus a continuous...
[ { "created": "Tue, 21 Aug 2018 13:39:48 GMT", "version": "v1" } ]
2018-08-22
[ [ "Dimitrova", "Desislava", "" ], [ "Liagouris", "John", "" ], [ "Wicki", "Sebastian", "" ], [ "Hoffmann", "Moritz", "" ], [ "Kalavri", "Vasiliki", "" ], [ "Roscoe", "Timothy", "" ] ]
Routing controllers must react quickly to failures, reconfigurations and workload or policy changes, to ensure service performance and cost-efficient network operation. We propose a general execution model which views routing as an incremental data-parallel computation on a graph-based network model plus a continuous s...
1406.1774
Toufiq Parag
Toufiq Parag, Stephen Plaza, Louis Scheffer (Janelia Farm Research Campus- HHMI)
Small Sample Learning of Superpixel Classifiers for EM Segmentation- Extended Version
Accepted for MICCAI 2014
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pixel and superpixel classifiers have become essential tools for EM segmentation algorithms. Training these classifiers remains a major bottleneck primarily due to the requirement of completely annotating the dataset which is tedious, error-prone and costly. In this paper, we propose an interactive learning scheme fo...
[ { "created": "Fri, 6 Jun 2014 18:59:58 GMT", "version": "v1" }, { "created": "Fri, 13 Jun 2014 22:05:57 GMT", "version": "v2" } ]
2014-06-17
[ [ "Parag", "Toufiq", "", "Janelia Farm Research\n Campus- HHMI" ], [ "Plaza", "Stephen", "", "Janelia Farm Research\n Campus- HHMI" ], [ "Scheffer", "Louis", "", "Janelia Farm Research\n Campus- HHMI" ] ]
Pixel and superpixel classifiers have become essential tools for EM segmentation algorithms. Training these classifiers remains a major bottleneck primarily due to the requirement of completely annotating the dataset which is tedious, error-prone and costly. In this paper, we propose an interactive learning scheme for ...
1611.09906
Saverio Perugini
Brandon M. Williams and Saverio Perugini
Revisiting the Futamura Projections: A Diagrammatic Approach
20 pages, 11 figures, 3 tables; pre-print of published version in Theoretical and Applied Informatics
B.M. Williams & Perugini, S. (2016) Revisiting the Futamura Projections: A diagrammatic approach. Theoretical and Applied Informatics, 28(4), 15-32
10.20904/284015
null
cs.PL cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The advent of language implementation tools such as PyPy and Truffle/Graal have reinvigorated and broadened interest in topics related to automatic compiler generation and optimization. Given this broader interest, we revisit the Futamura Projections using a novel diagram scheme. Through these diagrams we emphasize t...
[ { "created": "Tue, 29 Nov 2016 21:56:34 GMT", "version": "v1" }, { "created": "Wed, 29 Mar 2017 00:00:13 GMT", "version": "v2" }, { "created": "Tue, 20 Mar 2018 22:38:16 GMT", "version": "v3" } ]
2018-03-22
[ [ "Williams", "Brandon M.", "" ], [ "Perugini", "Saverio", "" ] ]
The advent of language implementation tools such as PyPy and Truffle/Graal have reinvigorated and broadened interest in topics related to automatic compiler generation and optimization. Given this broader interest, we revisit the Futamura Projections using a novel diagram scheme. Through these diagrams we emphasize the...
2209.07706
Junliang Luo
Junliang Luo, Yongzheng Jia, Xue Liu
Understanding NFT Price Moves through Tweets Keywords Analysis
null
null
10.1145/3582515.3609562
null
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Non-Fungible Token (NFT) is evolving with the rise of the cryptocurrency market and the development of blockchain techniques, which leads to an emerging NFT market that has become prosperous rapidly then followed by a cooldown. Nevertheless, the overall rise procedure of the NFT market has not been well understood. T...
[ { "created": "Fri, 16 Sep 2022 04:05:47 GMT", "version": "v1" }, { "created": "Mon, 27 Feb 2023 04:53:46 GMT", "version": "v2" }, { "created": "Fri, 3 Mar 2023 18:15:12 GMT", "version": "v3" } ]
2023-09-21
[ [ "Luo", "Junliang", "" ], [ "Jia", "Yongzheng", "" ], [ "Liu", "Xue", "" ] ]
Non-Fungible Token (NFT) is evolving with the rise of the cryptocurrency market and the development of blockchain techniques, which leads to an emerging NFT market that has become prosperous rapidly then followed by a cooldown. Nevertheless, the overall rise procedure of the NFT market has not been well understood. To ...
2305.01578
Arsenii Gorin
Arsenii Gorin, Cem Subakan, Sajjad Abdoli, Junhao Wang, Samantha Latremouille, Charles Onu
Self-supervised learning for infant cry analysis
Accepted to IEEE ICASSP 2023 workshop Self-supervision in Audio, Speech and Beyond
null
null
null
cs.SD cs.AI cs.CL eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we explore self-supervised learning (SSL) for analyzing a first-of-its-kind database of cry recordings containing clinical indications of more than a thousand newborns. Specifically, we target cry-based detection of neurological injury as well as identification of cry triggers such as pain, hunger, and...
[ { "created": "Tue, 2 May 2023 16:27:18 GMT", "version": "v1" } ]
2023-05-03
[ [ "Gorin", "Arsenii", "" ], [ "Subakan", "Cem", "" ], [ "Abdoli", "Sajjad", "" ], [ "Wang", "Junhao", "" ], [ "Latremouille", "Samantha", "" ], [ "Onu", "Charles", "" ] ]
In this paper, we explore self-supervised learning (SSL) for analyzing a first-of-its-kind database of cry recordings containing clinical indications of more than a thousand newborns. Specifically, we target cry-based detection of neurological injury as well as identification of cry triggers such as pain, hunger, and d...
2305.03112
Lechao Cheng
Jingxuan He, Lechao Cheng, Chaowei Fang, Dingwen Zhang, Zhangye Wang, Wei Chen
Mitigating Undisciplined Over-Smoothing in Transformer for Weakly Supervised Semantic Segmentation
10 pages, 10 figures
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
A surge of interest has emerged in weakly supervised semantic segmentation due to its remarkable efficiency in recent years. Existing approaches based on transformers mainly focus on exploring the affinity matrix to boost CAMs with global relationships. While in this work, we first perform a scrupulous examination to...
[ { "created": "Thu, 4 May 2023 19:11:33 GMT", "version": "v1" } ]
2023-05-08
[ [ "He", "Jingxuan", "" ], [ "Cheng", "Lechao", "" ], [ "Fang", "Chaowei", "" ], [ "Zhang", "Dingwen", "" ], [ "Wang", "Zhangye", "" ], [ "Chen", "Wei", "" ] ]
A surge of interest has emerged in weakly supervised semantic segmentation due to its remarkable efficiency in recent years. Existing approaches based on transformers mainly focus on exploring the affinity matrix to boost CAMs with global relationships. While in this work, we first perform a scrupulous examination towa...
2212.04025
Charline Le Lan
Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces
8 pages in main content, 2 pages of bibliography and 5 pages in Appendix
null
null
null
cs.LG cs.AI stat.ML
http://creativecommons.org/licenses/by/4.0/
Many machine learning problems encode their data as a matrix with a possibly very large number of rows and columns. In several applications like neuroscience, image compression or deep reinforcement learning, the principal subspace of such a matrix provides a useful, low-dimensional representation of individual data....
[ { "created": "Thu, 8 Dec 2022 01:26:47 GMT", "version": "v1" } ]
2022-12-09
[ [ "Lan", "Charline Le", "" ], [ "Greaves", "Joshua", "" ], [ "Farebrother", "Jesse", "" ], [ "Rowland", "Mark", "" ], [ "Pedregosa", "Fabian", "" ], [ "Agarwal", "Rishabh", "" ], [ "Bellemare", "Marc G.", "" ...
Many machine learning problems encode their data as a matrix with a possibly very large number of rows and columns. In several applications like neuroscience, image compression or deep reinforcement learning, the principal subspace of such a matrix provides a useful, low-dimensional representation of individual data. H...
2210.17490
Artyom Grigoryan
Artyom M. Grigoryan, Sos S. Agaian, Karen Panetta
Quantum-Inspired Edge Detection Algorithms Implementation using New Dynamic Visual Data Representation and Short-Length Convolution Computation
11 pages, 11 figures
null
null
null
cs.CV math.QA
http://creativecommons.org/licenses/by/4.0/
As the availability of imagery data continues to swell, so do the demands on transmission, storage and processing power. Processing requirements to handle this plethora of data is quickly outpacing the utility of conventional processing techniques. Transitioning to quantum processing and algorithms that offer promisi...
[ { "created": "Mon, 31 Oct 2022 17:13:27 GMT", "version": "v1" } ]
2022-11-01
[ [ "Grigoryan", "Artyom M.", "" ], [ "Agaian", "Sos S.", "" ], [ "Panetta", "Karen", "" ] ]
As the availability of imagery data continues to swell, so do the demands on transmission, storage and processing power. Processing requirements to handle this plethora of data is quickly outpacing the utility of conventional processing techniques. Transitioning to quantum processing and algorithms that offer promising...
1809.01872
Ikram Boukhedimi
Ikram Boukhedimi, Abla Kammoun, Mohamed-Slim Alouini
LMMSE Receivers in Uplink Massive MIMO Systems with Correlated Rician Fading
32 pages, 8 figures, accepted to be published in IEEE Transactions on Communications
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We carry out a theoretical analysis of the uplink (UL) of a massive MIMO system with per-user channel correlation and Rician fading, using two processing approaches. Firstly, we examine the linear minimum-mean-square-error receiver under training-based imperfect channel estimates. Secondly, we propose a statistical c...
[ { "created": "Thu, 6 Sep 2018 08:19:51 GMT", "version": "v1" } ]
2018-09-07
[ [ "Boukhedimi", "Ikram", "" ], [ "Kammoun", "Abla", "" ], [ "Alouini", "Mohamed-Slim", "" ] ]
We carry out a theoretical analysis of the uplink (UL) of a massive MIMO system with per-user channel correlation and Rician fading, using two processing approaches. Firstly, we examine the linear minimum-mean-square-error receiver under training-based imperfect channel estimates. Secondly, we propose a statistical com...
1804.04868
Andr\'e Calero Valdez
Andr\'e Calero Valdez, Martina Ziefle
The Users' Perspective on the Privacy-Utility Trade-offs in Health Recommender Systems
32 pages, 12 figures
null
10.1016/j.ijhcs.2018.04.003
null
cs.CY cs.CR cs.HC
http://creativecommons.org/licenses/by-nc-sa/4.0/
Privacy is a major good for users of personalized services such as recommender systems. When applied to the field of health informatics, privacy concerns of users may be amplified, but the possible utility of such services is also high. Despite availability of technologies such as k-anonymity, differential privacy, p...
[ { "created": "Fri, 13 Apr 2018 10:03:09 GMT", "version": "v1" } ]
2024-06-14
[ [ "Valdez", "André Calero", "" ], [ "Ziefle", "Martina", "" ] ]
Privacy is a major good for users of personalized services such as recommender systems. When applied to the field of health informatics, privacy concerns of users may be amplified, but the possible utility of such services is also high. Despite availability of technologies such as k-anonymity, differential privacy, pri...
1903.00041
George Foster
Gaurav Kumar, George Foster, Colin Cherry, Maxim Krikun
Reinforcement Learning based Curriculum Optimization for Neural Machine Translation
NAACL 2019 short paper. Reviewer comments not yet addressed
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
We consider the problem of making efficient use of heterogeneous training data in neural machine translation (NMT). Specifically, given a training dataset with a sentence-level feature such as noise, we seek an optimal curriculum, or order for presenting examples to the system during training. Our curriculum framewor...
[ { "created": "Thu, 28 Feb 2019 19:35:09 GMT", "version": "v1" } ]
2019-03-04
[ [ "Kumar", "Gaurav", "" ], [ "Foster", "George", "" ], [ "Cherry", "Colin", "" ], [ "Krikun", "Maxim", "" ] ]
We consider the problem of making efficient use of heterogeneous training data in neural machine translation (NMT). Specifically, given a training dataset with a sentence-level feature such as noise, we seek an optimal curriculum, or order for presenting examples to the system during training. Our curriculum framework ...
1602.05908
Rong Ge
Anima Anandkumar, Rong Ge
Efficient approaches for escaping higher order saddle points in non-convex optimization
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Local search heuristics for non-convex optimizations are popular in applied machine learning. However, in general it is hard to guarantee that such algorithms even converge to a local minimum, due to the existence of complicated saddle point structures in high dimensions. Many functions have degenerate saddle points ...
[ { "created": "Thu, 18 Feb 2016 18:52:15 GMT", "version": "v1" } ]
2016-02-19
[ [ "Anandkumar", "Anima", "" ], [ "Ge", "Rong", "" ] ]
Local search heuristics for non-convex optimizations are popular in applied machine learning. However, in general it is hard to guarantee that such algorithms even converge to a local minimum, due to the existence of complicated saddle point structures in high dimensions. Many functions have degenerate saddle points su...
2004.06660
Paul Michel
Keita Kurita, Paul Michel, Graham Neubig
Weight Poisoning Attacks on Pre-trained Models
Published as a long paper at ACL 2020
null
null
null
cs.LG cs.CL cs.CR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, NLP has seen a surge in the usage of large pre-trained models. Users download weights of models pre-trained on large datasets, then fine-tune the weights on a task of their choice. This raises the question of whether downloading untrusted pre-trained weights can pose a security threat. In this paper, we sho...
[ { "created": "Tue, 14 Apr 2020 16:51:42 GMT", "version": "v1" } ]
2020-04-15
[ [ "Kurita", "Keita", "" ], [ "Michel", "Paul", "" ], [ "Neubig", "Graham", "" ] ]
Recently, NLP has seen a surge in the usage of large pre-trained models. Users download weights of models pre-trained on large datasets, then fine-tune the weights on a task of their choice. This raises the question of whether downloading untrusted pre-trained weights can pose a security threat. In this paper, we show ...
2312.08962
Zhiyuan You
Zhiyuan You, Zheyuan Li, Jinjin Gu, Zhenfei Yin, Tianfan Xue, Chao Dong
Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Models
Accepted to ECCV2024, Camera Ready Version
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a Depicted image Quality Assessment method (DepictQA), overcoming the constraints of traditional score-based methods. DepictQA allows for detailed, language-based, human-like evaluation of image quality by leveraging Multi-modal Large Language Models (MLLMs). Unlike conventional Image Quality Assessment ...
[ { "created": "Thu, 14 Dec 2023 14:10:02 GMT", "version": "v1" }, { "created": "Sun, 10 Mar 2024 09:18:17 GMT", "version": "v2" }, { "created": "Sun, 14 Jul 2024 12:33:05 GMT", "version": "v3" } ]
2024-07-16
[ [ "You", "Zhiyuan", "" ], [ "Li", "Zheyuan", "" ], [ "Gu", "Jinjin", "" ], [ "Yin", "Zhenfei", "" ], [ "Xue", "Tianfan", "" ], [ "Dong", "Chao", "" ] ]
We introduce a Depicted image Quality Assessment method (DepictQA), overcoming the constraints of traditional score-based methods. DepictQA allows for detailed, language-based, human-like evaluation of image quality by leveraging Multi-modal Large Language Models (MLLMs). Unlike conventional Image Quality Assessment (I...
1307.1872
Ibrahim Sabek
Ibrahim Sabek, Noha A. Yousri, Nagwa Elmakky and Mona Habib
Intelligent Hybrid Man-Machine Translation Quality Estimation
8 pages, 3 figures, 5 tables
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inferring evaluation scores based on human judgments is invaluable compared to using current evaluation metrics which are not suitable for real-time applications e.g. post-editing. However, these judgments are much more expensive to collect especially from expert translators, compared to evaluation based on indicator...
[ { "created": "Sun, 7 Jul 2013 15:04:11 GMT", "version": "v1" } ]
2013-07-09
[ [ "Sabek", "Ibrahim", "" ], [ "Yousri", "Noha A.", "" ], [ "Elmakky", "Nagwa", "" ], [ "Habib", "Mona", "" ] ]
Inferring evaluation scores based on human judgments is invaluable compared to using current evaluation metrics which are not suitable for real-time applications e.g. post-editing. However, these judgments are much more expensive to collect especially from expert translators, compared to evaluation based on indicators ...
1902.06085
Meiyu Li
Meiyu Li, Hailiang Tang, Michael D. Chan, Xiaobo Zhou, and Xiaohua Qian
DC-AL GAN: Pseudoprogression and True Tumor Progression of Glioblastoma Multiform Image Classification Based on DCGAN and AlexNet
null
null
10.1002/mp.14003
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) after receiving the standard treatment. In the course of post-treatment magnetic resonance imaging (MRI), PsP exhibits similarities in shape and intensity to the true tumor progression (TTP) of GBM. So, these similarities pose cha...
[ { "created": "Sat, 16 Feb 2019 10:43:33 GMT", "version": "v1" }, { "created": "Tue, 26 Feb 2019 13:54:13 GMT", "version": "v2" }, { "created": "Wed, 15 May 2019 05:54:26 GMT", "version": "v3" }, { "created": "Sat, 18 May 2019 05:48:12 GMT", "version": "v4" } ]
2020-07-01
[ [ "Li", "Meiyu", "" ], [ "Tang", "Hailiang", "" ], [ "Chan", "Michael D.", "" ], [ "Zhou", "Xiaobo", "" ], [ "Qian", "Xiaohua", "" ] ]
Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) after receiving the standard treatment. In the course of post-treatment magnetic resonance imaging (MRI), PsP exhibits similarities in shape and intensity to the true tumor progression (TTP) of GBM. So, these similarities pose chall...
2403.16246
Subhodip Panda
Subhodip Panda and Shashwat Sourav and Prathosh A.P
Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective
null
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
In order to adhere to regulatory standards governing individual data privacy and safety, machine learning models must systematically eliminate information derived from specific subsets of a user's training data that can no longer be utilized. The emerging discipline of Machine Unlearning has arisen as a pivotal area ...
[ { "created": "Sun, 24 Mar 2024 17:33:22 GMT", "version": "v1" } ]
2024-03-26
[ [ "Panda", "Subhodip", "" ], [ "Sourav", "Shashwat", "" ], [ "P", "Prathosh A.", "" ] ]
In order to adhere to regulatory standards governing individual data privacy and safety, machine learning models must systematically eliminate information derived from specific subsets of a user's training data that can no longer be utilized. The emerging discipline of Machine Unlearning has arisen as a pivotal area of...
2102.09978
Zining Zhang
Zining Zhang, Bingsheng He, Zhenjie Zhang
TransMask: A Compact and Fast Speech Separation Model Based on Transformer
Accepted in ICASSP2021
null
null
null
cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Speech separation is an important problem in speech processing, which targets to separate and generate clean speech from a mixed audio containing speech from different speakers. Empowered by the deep learning technologies over sequence-to-sequence domain, recent neural speech separation models are now capable of gene...
[ { "created": "Fri, 19 Feb 2021 15:19:24 GMT", "version": "v1" } ]
2021-02-22
[ [ "Zhang", "Zining", "" ], [ "He", "Bingsheng", "" ], [ "Zhang", "Zhenjie", "" ] ]
Speech separation is an important problem in speech processing, which targets to separate and generate clean speech from a mixed audio containing speech from different speakers. Empowered by the deep learning technologies over sequence-to-sequence domain, recent neural speech separation models are now capable of genera...
2007.03970
Matthias Langer
Matthias Langer, Zhen He, Wenny Rahayu, and Yanbo Xue
Distributed Training of Deep Learning Models: A Taxonomic Perspective
null
IEEE Transactions on Parallel and Distributed Systems, 2020, Volume: 31, Issue: 12, Pages: 2802-2818
10.1109/TPDS.2020.3003307
null
cs.DC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distributed deep learning systems (DDLS) train deep neural network models by utilizing the distributed resources of a cluster. Developers of DDLS are required to make many decisions to process their particular workloads in their chosen environment efficiently. The advent of GPU-based deep learning, the ever-increasin...
[ { "created": "Wed, 8 Jul 2020 08:56:58 GMT", "version": "v1" } ]
2020-07-09
[ [ "Langer", "Matthias", "" ], [ "He", "Zhen", "" ], [ "Rahayu", "Wenny", "" ], [ "Xue", "Yanbo", "" ] ]
Distributed deep learning systems (DDLS) train deep neural network models by utilizing the distributed resources of a cluster. Developers of DDLS are required to make many decisions to process their particular workloads in their chosen environment efficiently. The advent of GPU-based deep learning, the ever-increasing ...
2105.14127
Michael Gimelfarb Mr.
Michael Gimelfarb, Andr\'e Barreto, Scott Sanner, Chi-Guhn Lee
Risk-Aware Transfer in Reinforcement Learning using Successor Features
null
null
null
null
cs.LG cs.AI cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sample efficiency and risk-awareness are central to the development of practical reinforcement learning (RL) for complex decision-making. The former can be addressed by transfer learning and the latter by optimizing some utility function of the return. However, the problem of transferring skills in a risk-aware manne...
[ { "created": "Fri, 28 May 2021 22:22:03 GMT", "version": "v1" } ]
2021-06-01
[ [ "Gimelfarb", "Michael", "" ], [ "Barreto", "André", "" ], [ "Sanner", "Scott", "" ], [ "Lee", "Chi-Guhn", "" ] ]
Sample efficiency and risk-awareness are central to the development of practical reinforcement learning (RL) for complex decision-making. The former can be addressed by transfer learning and the latter by optimizing some utility function of the return. However, the problem of transferring skills in a risk-aware manner ...
1907.02964
Carlos Brys Mg.
Carlos Roberto Brys, Jos\'e F. Aldana-Montes, David Luis La Red Mart\'inez
Un Modelo Ontol\'ogico para el Gobierno Electr\'onico
10 pages, in Spanish
null
null
null
cs.DL cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Decision making often requires information that must be Provided with the rich data format. Addressing these new requirements appropriately makes it necessary for government agencies to orchestrate large amounts of information from different sources and formats, to be efficiently delivered through the devices commonl...
[ { "created": "Thu, 4 Jul 2019 21:42:26 GMT", "version": "v1" } ]
2019-07-09
[ [ "Brys", "Carlos Roberto", "" ], [ "Aldana-Montes", "José F.", "" ], [ "Martínez", "David Luis La Red", "" ] ]
Decision making often requires information that must be Provided with the rich data format. Addressing these new requirements appropriately makes it necessary for government agencies to orchestrate large amounts of information from different sources and formats, to be efficiently delivered through the devices commonly ...
2209.12648
Aykut Isleyen
Aykut \.I\c{s}leyen and Nathan van de Wouw and \"Om\"ur Arslan
Feedback Motion Prediction for Safe Unicycle Robot Navigation
11 pages, 5 figures, extended version of a paper submitted to a conference publication
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As a simple and robust mobile robot base, differential drive robots that can be modelled as a kinematic unicycle find significant applications in logistics and service robotics in both industrial and domestic settings. Safe robot navigation around obstacles is an essential skill for such unicycle robots to perform di...
[ { "created": "Mon, 26 Sep 2022 12:52:48 GMT", "version": "v1" }, { "created": "Wed, 5 Apr 2023 21:14:25 GMT", "version": "v2" }, { "created": "Mon, 31 Jul 2023 16:09:21 GMT", "version": "v3" } ]
2023-08-01
[ [ "İşleyen", "Aykut", "" ], [ "van de Wouw", "Nathan", "" ], [ "Arslan", "Ömür", "" ] ]
As a simple and robust mobile robot base, differential drive robots that can be modelled as a kinematic unicycle find significant applications in logistics and service robotics in both industrial and domestic settings. Safe robot navigation around obstacles is an essential skill for such unicycle robots to perform dive...
2306.05696
Jielin Qiu
Jielin Qiu, Mengdi Xu, William Han, Seungwhan Moon, Ding Zhao
Embodied Executable Policy Learning with Language-based Scene Summarization
15 pages. arXiv admin note: text overlap with arXiv:2107.06912 by other authors
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large Language models (LLMs) have shown remarkable success in assisting robot learning tasks, i.e., complex household planning. However, the performance of pretrained LLMs heavily relies on domain-specific templated text data, which may be infeasible in real-world robot learning tasks with image-based observations. M...
[ { "created": "Fri, 9 Jun 2023 06:34:09 GMT", "version": "v1" } ]
2023-06-12
[ [ "Qiu", "Jielin", "" ], [ "Xu", "Mengdi", "" ], [ "Han", "William", "" ], [ "Moon", "Seungwhan", "" ], [ "Zhao", "Ding", "" ] ]
Large Language models (LLMs) have shown remarkable success in assisting robot learning tasks, i.e., complex household planning. However, the performance of pretrained LLMs heavily relies on domain-specific templated text data, which may be infeasible in real-world robot learning tasks with image-based observations. Mor...
2101.10417
Dragi Kimovski
Dragi Kimovski, Roland Math\'a, Josef Hammer, Narges Mehran, Hermann Hellwagner and Radu Prodan
Cloud, Fog or Edge: Where to Compute?
null
IEEE Internet Computing 2021
10.1109/MIC.2021.3050613
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The computing continuum extends the high-performance cloud data centers with energy-efficient and low-latency devices close to the data sources located at the edge of the network. However, the heterogeneity of the computing continuum raises multiple challenges related to application management. These include where to...
[ { "created": "Mon, 25 Jan 2021 21:05:00 GMT", "version": "v1" } ]
2021-01-28
[ [ "Kimovski", "Dragi", "" ], [ "Mathá", "Roland", "" ], [ "Hammer", "Josef", "" ], [ "Mehran", "Narges", "" ], [ "Hellwagner", "Hermann", "" ], [ "Prodan", "Radu", "" ] ]
The computing continuum extends the high-performance cloud data centers with energy-efficient and low-latency devices close to the data sources located at the edge of the network. However, the heterogeneity of the computing continuum raises multiple challenges related to application management. These include where to o...
2312.08274
Songchi Zhou
Songchi Zhou, Sheng Yu
High-throughput Biomedical Relation Extraction for Semi-Structured Web Articles Empowered by Large Language Models
null
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Objective: To develop a high-throughput biomedical relation extraction system that takes advantage of the large language models'(LLMs) reading comprehension ability and biomedical world knowledge in a scalable and evidential manner. Methods: We formulate the relation extraction task as binary classifications for larg...
[ { "created": "Wed, 13 Dec 2023 16:43:41 GMT", "version": "v1" }, { "created": "Thu, 14 Dec 2023 07:28:03 GMT", "version": "v2" }, { "created": "Fri, 15 Dec 2023 07:25:34 GMT", "version": "v3" }, { "created": "Tue, 26 Mar 2024 10:36:31 GMT", "version": "v4" } ]
2024-03-27
[ [ "Zhou", "Songchi", "" ], [ "Yu", "Sheng", "" ] ]
Objective: To develop a high-throughput biomedical relation extraction system that takes advantage of the large language models'(LLMs) reading comprehension ability and biomedical world knowledge in a scalable and evidential manner. Methods: We formulate the relation extraction task as binary classifications for large ...
1712.10136
Koustav Mullick Mr.
Koustav Mullick and Anoop M. Namboodiri
Learning Deep and Compact Models for Gesture Recognition
Accepted at 2017 IEEE International Conference on Image Processing (ICIP 2017)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We look at the problem of developing a compact and accurate model for gesture recognition from videos in a deep-learning framework. Towards this we propose a joint 3DCNN-LSTM model that is end-to-end trainable and is shown to be better suited to capture the dynamic information in actions. The solution achieves close ...
[ { "created": "Fri, 29 Dec 2017 07:38:43 GMT", "version": "v1" } ]
2018-01-01
[ [ "Mullick", "Koustav", "" ], [ "Namboodiri", "Anoop M.", "" ] ]
We look at the problem of developing a compact and accurate model for gesture recognition from videos in a deep-learning framework. Towards this we propose a joint 3DCNN-LSTM model that is end-to-end trainable and is shown to be better suited to capture the dynamic information in actions. The solution achieves close to...
2303.08717
Sara Rojas
Sara Rojas, Jesus Zarzar, Juan Camilo Perez, Artsiom Sanakoyeu, Ali Thabet, Albert Pumarola, and Bernard Ghanem
Re-ReND: Real-time Rendering of NeRFs across Devices
null
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a novel approach for rendering a pre-trained Neural Radiance Field (NeRF) in real-time on resource-constrained devices. We introduce Re-ReND, a method enabling Real-time Rendering of NeRFs across Devices. Re-ReND is designed to achieve real-time performance by converting the NeRF into a representa...
[ { "created": "Wed, 15 Mar 2023 15:59:41 GMT", "version": "v1" } ]
2023-03-16
[ [ "Rojas", "Sara", "" ], [ "Zarzar", "Jesus", "" ], [ "Perez", "Juan Camilo", "" ], [ "Sanakoyeu", "Artsiom", "" ], [ "Thabet", "Ali", "" ], [ "Pumarola", "Albert", "" ], [ "Ghanem", "Bernard", "" ] ]
This paper proposes a novel approach for rendering a pre-trained Neural Radiance Field (NeRF) in real-time on resource-constrained devices. We introduce Re-ReND, a method enabling Real-time Rendering of NeRFs across Devices. Re-ReND is designed to achieve real-time performance by converting the NeRF into a representati...
2012.14230
Bo Li
Bo Li, Wiro J. Niessen, Stefan Klein, Marius de Groot, M. Arfan Ikram, Meike W. Vernooij, Esther E. Bron
Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration
To appear in NeuroImage
null
10.1016/j.neuroimage.2021.118004
null
cs.CV cs.AI eess.IV
http://creativecommons.org/licenses/by-nc-nd/4.0/
This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class segmentation and nonlinear registration. Segmentation and registration are modeled using a convolut...
[ { "created": "Mon, 28 Dec 2020 13:48:21 GMT", "version": "v1" }, { "created": "Fri, 23 Apr 2021 11:06:25 GMT", "version": "v2" } ]
2021-04-26
[ [ "Li", "Bo", "" ], [ "Niessen", "Wiro J.", "" ], [ "Klein", "Stefan", "" ], [ "de Groot", "Marius", "" ], [ "Ikram", "M. Arfan", "" ], [ "Vernooij", "Meike W.", "" ], [ "Bron", "Esther E.", "" ] ]
This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class segmentation and nonlinear registration. Segmentation and registration are modeled using a convolutio...
2104.05185
Pengcheng Xia
Pengcheng Xia, Haoyu Wang, Zhou Yu, Xinyu Liu, Xiapu Luo, Guoai Xu
Ethereum Name Service: the Good, the Bad, and the Ugly
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
DNS has always been criticized for its inherent design flaws, making the system vulnerable to kinds of attacks. Besides, DNS domain names are not fully controlled by the users, which can be easily taken down by the authorities and registrars. Since blockchain has its unique properties like immutability and decentrali...
[ { "created": "Mon, 12 Apr 2021 03:39:01 GMT", "version": "v1" } ]
2021-04-13
[ [ "Xia", "Pengcheng", "" ], [ "Wang", "Haoyu", "" ], [ "Yu", "Zhou", "" ], [ "Liu", "Xinyu", "" ], [ "Luo", "Xiapu", "" ], [ "Xu", "Guoai", "" ] ]
DNS has always been criticized for its inherent design flaws, making the system vulnerable to kinds of attacks. Besides, DNS domain names are not fully controlled by the users, which can be easily taken down by the authorities and registrars. Since blockchain has its unique properties like immutability and decentraliza...
2012.05457
Guanya Shi
Guanya Shi, Wolfgang H\"onig, Xichen Shi, Yisong Yue, Soon-Jo Chung
Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions
Accepted by IEEE Transactions on Robotics (T-RO), 2021. Video is available at https://youtu.be/Y02juH6BDxo
null
null
null
cs.RO cs.AI cs.LG cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present Neural-Swarm2, a learning-based method for motion planning and control that allows heterogeneous multirotors in a swarm to safely fly in close proximity. Such operation for drones is challenging due to complex aerodynamic interaction forces, such as downwash generated by nearby drones and ground effect. Co...
[ { "created": "Thu, 10 Dec 2020 05:08:31 GMT", "version": "v1" }, { "created": "Fri, 16 Jul 2021 01:24:46 GMT", "version": "v2" } ]
2021-07-19
[ [ "Shi", "Guanya", "" ], [ "Hönig", "Wolfgang", "" ], [ "Shi", "Xichen", "" ], [ "Yue", "Yisong", "" ], [ "Chung", "Soon-Jo", "" ] ]
We present Neural-Swarm2, a learning-based method for motion planning and control that allows heterogeneous multirotors in a swarm to safely fly in close proximity. Such operation for drones is challenging due to complex aerodynamic interaction forces, such as downwash generated by nearby drones and ground effect. Conv...
2310.17743
Yajing Luo
Hanqing Wang, Yajing Luo, Boya Xiong, Guanhua Chen, Yun Chen
StyleBART: Decorate Pretrained Model with Style Adapters for Unsupervised Stylistic Headline Generation
Findings of EMNLP 2023
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Stylistic headline generation is the task to generate a headline that not only summarizes the content of an article, but also reflects a desired style that attracts users. As style-specific article-headline pairs are scarce, previous researches focus on unsupervised approaches with a standard headline generation data...
[ { "created": "Thu, 26 Oct 2023 19:31:22 GMT", "version": "v1" }, { "created": "Mon, 13 Nov 2023 06:38:53 GMT", "version": "v2" } ]
2023-11-14
[ [ "Wang", "Hanqing", "" ], [ "Luo", "Yajing", "" ], [ "Xiong", "Boya", "" ], [ "Chen", "Guanhua", "" ], [ "Chen", "Yun", "" ] ]
Stylistic headline generation is the task to generate a headline that not only summarizes the content of an article, but also reflects a desired style that attracts users. As style-specific article-headline pairs are scarce, previous researches focus on unsupervised approaches with a standard headline generation datase...
1107.1206
EPTCS
Mathieu Tracol (IST Austria), Jos\'ee Desharnais (Departement d'informatique et de g\'enie logiciel, Universit\'e Laval, Qu\'ebec, Canada), Abir Zhioua (Departement d'informatique et de g\'enie logiciel, Universit\'e Laval, Qu\'ebec, Canada)
Computing Distances between Probabilistic Automata
In Proceedings QAPL 2011, arXiv:1107.0746
EPTCS 57, 2011, pp. 148-162
10.4204/EPTCS.57.11
null
cs.FL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present relaxed notions of simulation and bisimulation on Probabilistic Automata (PA), that allow some error epsilon. When epsilon is zero we retrieve the usual notions of bisimulation and simulation on PAs. We give logical characterisations of these notions by choosing suitable logics which differ from the elemen...
[ { "created": "Wed, 6 Jul 2011 17:55:31 GMT", "version": "v1" } ]
2011-07-07
[ [ "Tracol", "Mathieu", "", "IST Austria" ], [ "Desharnais", "Josée", "", "Departement\n d'informatique et de génie logiciel, Université Laval, Québec, Canada" ], [ "Zhioua", "Abir", "", "Departement d'informatique et de génie logiciel, Université\n Laval, Qu...
We present relaxed notions of simulation and bisimulation on Probabilistic Automata (PA), that allow some error epsilon. When epsilon is zero we retrieve the usual notions of bisimulation and simulation on PAs. We give logical characterisations of these notions by choosing suitable logics which differ from the elementa...
2311.02311
Terrance Yu-Hao Chen
Yi-Zih Chen, Terrance Yu-Hao Chen, Po-Jung Su, Chi-Ting Liu
A Brief Survey of Open Radio Access Network (O-RAN) Security
null
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
Open Radio Access Network (O-RAN), a novel architecture that separates the traditional radio access network (RAN) into multiple disaggregated components, leads a revolution in the telecommunication ecosystems. Compared to the traditional RAN, the proposed O-RAN paradigm is more flexible and more cost-effective for th...
[ { "created": "Sat, 4 Nov 2023 03:29:03 GMT", "version": "v1" } ]
2023-11-07
[ [ "Chen", "Yi-Zih", "" ], [ "Chen", "Terrance Yu-Hao", "" ], [ "Su", "Po-Jung", "" ], [ "Liu", "Chi-Ting", "" ] ]
Open Radio Access Network (O-RAN), a novel architecture that separates the traditional radio access network (RAN) into multiple disaggregated components, leads a revolution in the telecommunication ecosystems. Compared to the traditional RAN, the proposed O-RAN paradigm is more flexible and more cost-effective for the ...
1706.03675
William Weir
William H. Weir, Scott Emmons, Ryan Gibson, Dane Taylor, Peter J. Mucha
Post-processing partitions to identify domains of modularity optimization
http://www.mdpi.com/1999-4893/10/3/93
Algorithms 10, no. 3: 93 (2017)
10.3390/a10030093
null
cs.SI physics.soc-ph
http://creativecommons.org/licenses/by/4.0/
We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of possibly various computational heuristics. Given a set of partitions, CHAMP identifies the domain of modularity optimization for each par...
[ { "created": "Mon, 12 Jun 2017 14:57:25 GMT", "version": "v1" }, { "created": "Tue, 13 Jun 2017 11:51:25 GMT", "version": "v2" }, { "created": "Thu, 27 Jul 2017 19:25:02 GMT", "version": "v3" }, { "created": "Mon, 21 Aug 2017 12:03:30 GMT", "version": "v4" } ]
2017-08-22
[ [ "Weir", "William H.", "" ], [ "Emmons", "Scott", "" ], [ "Gibson", "Ryan", "" ], [ "Taylor", "Dane", "" ], [ "Mucha", "Peter J.", "" ] ]
We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of possibly various computational heuristics. Given a set of partitions, CHAMP identifies the domain of modularity optimization for each parti...
2402.12431
Amelie W\"uhrl
Amelie W\"uhrl, Dustin Wright, Roman Klinger, Isabelle Augenstein
Understanding Fine-grained Distortions in Reports of Scientific Findings
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Distorted science communication harms individuals and society as it can lead to unhealthy behavior change and decrease trust in scientific institutions. Given the rapidly increasing volume of science communication in recent years, a fine-grained understanding of how findings from scientific publications are reported ...
[ { "created": "Mon, 19 Feb 2024 19:00:01 GMT", "version": "v1" } ]
2024-02-21
[ [ "Wührl", "Amelie", "" ], [ "Wright", "Dustin", "" ], [ "Klinger", "Roman", "" ], [ "Augenstein", "Isabelle", "" ] ]
Distorted science communication harms individuals and society as it can lead to unhealthy behavior change and decrease trust in scientific institutions. Given the rapidly increasing volume of science communication in recent years, a fine-grained understanding of how findings from scientific publications are reported to...
2010.01051
Sungbin Lim
Minsuk Shin, Hyungjoo Cho, Hyun-seok Min, Sungbin Lim
Neural Bootstrapper
19 pages, 13 figures. Accepted for NeurIPS 2021. Corresponding Author: Sungbin Lim
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bootstrapping has been a primary tool for ensemble and uncertainty quantification in machine learning and statistics. However, due to its nature of multiple training and resampling, bootstrapping deep neural networks is computationally burdensome; hence it has difficulties in practical application to the uncertainty ...
[ { "created": "Fri, 2 Oct 2020 15:30:04 GMT", "version": "v1" }, { "created": "Wed, 31 Mar 2021 02:37:47 GMT", "version": "v2" }, { "created": "Wed, 27 Oct 2021 07:11:08 GMT", "version": "v3" }, { "created": "Mon, 13 Dec 2021 17:35:06 GMT", "version": "v4" } ]
2021-12-14
[ [ "Shin", "Minsuk", "" ], [ "Cho", "Hyungjoo", "" ], [ "Min", "Hyun-seok", "" ], [ "Lim", "Sungbin", "" ] ]
Bootstrapping has been a primary tool for ensemble and uncertainty quantification in machine learning and statistics. However, due to its nature of multiple training and resampling, bootstrapping deep neural networks is computationally burdensome; hence it has difficulties in practical application to the uncertainty es...
2005.11459
Yuzhuo Liu
Yuzhuo Liu and Hangting Chen and Pengyuan Zhang
Power Pooling Operators and Confidence Learning for Semi-Supervised Sound Event Detection
null
null
null
null
cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, the involvement of synthetic strongly labeled data,weakly labeled data and unlabeled data has drawn much research attentionin semi-supervised sound event detection (SSED). Self-training models carry out predictions without strong annotations and then take predictions with high probabilities as pseudo...
[ { "created": "Sat, 23 May 2020 04:02:21 GMT", "version": "v1" } ]
2020-05-26
[ [ "Liu", "Yuzhuo", "" ], [ "Chen", "Hangting", "" ], [ "Zhang", "Pengyuan", "" ] ]
In recent years, the involvement of synthetic strongly labeled data,weakly labeled data and unlabeled data has drawn much research attentionin semi-supervised sound event detection (SSED). Self-training models carry out predictions without strong annotations and then take predictions with high probabilities as pseudo-l...
2212.11682
Tommaso Turchi
Robert D. Macredie, Martin Shepperd, Tommaso Turchi, Terry Young
Exploring Student Engagement and Outcomes: Experiences from Three Cycles of an Undergraduate Module
21 pages, 11 figures
null
null
null
cs.CY
http://creativecommons.org/licenses/by/4.0/
Many studies in educational data mining address specific learner groups, such as first-in-family to attend Higher Education, or focus on differences in characteristics such as gender or ethnicity, with the aim of predicting performance and designing interventions to improve outcomes. For Higher Education, this is ref...
[ { "created": "Thu, 22 Dec 2022 13:12:47 GMT", "version": "v1" } ]
2022-12-23
[ [ "Macredie", "Robert D.", "" ], [ "Shepperd", "Martin", "" ], [ "Turchi", "Tommaso", "" ], [ "Young", "Terry", "" ] ]
Many studies in educational data mining address specific learner groups, such as first-in-family to attend Higher Education, or focus on differences in characteristics such as gender or ethnicity, with the aim of predicting performance and designing interventions to improve outcomes. For Higher Education, this is refle...
2205.04103
Guillaume Theyssier
Samuel Nalin (LIFO), Guillaume Theyssier (I2M)
On Turedo Hierarchies and Intrinsic Universality
null
null
null
null
cs.CC cs.DM math.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper is about turedos, which are Turing machine whose head can move in the plane (or in a higher-dimensional space) but only in a selfavoiding way, by putting marks (letters) on visited positions and moving only to unmarked, therefore unvisited, positions. The key parameter of turedos is their lookup radius: th...
[ { "created": "Mon, 9 May 2022 08:09:08 GMT", "version": "v1" } ]
2022-05-10
[ [ "Nalin", "Samuel", "", "LIFO" ], [ "Theyssier", "Guillaume", "", "I2M" ] ]
This paper is about turedos, which are Turing machine whose head can move in the plane (or in a higher-dimensional space) but only in a selfavoiding way, by putting marks (letters) on visited positions and moving only to unmarked, therefore unvisited, positions. The key parameter of turedos is their lookup radius: the ...
1605.02474
Dongxiao Yu
Magnus M. Halldorsson and Tigran Tonoyan and Yuexuan Wang and Dongxiao Yu
Data Dissemination in Unified Dynamic Wireless Networks
28 pages, 2 figures
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We give efficient algorithms for the fundamental problems of Broadcast and Local Broadcast in dynamic wireless networks. We propose a general model of communication which captures and includes both fading models (like SINR) and graph-based models (such as quasi unit disc graphs, bounded-independence graphs, and proto...
[ { "created": "Mon, 9 May 2016 08:44:15 GMT", "version": "v1" } ]
2016-05-10
[ [ "Halldorsson", "Magnus M.", "" ], [ "Tonoyan", "Tigran", "" ], [ "Wang", "Yuexuan", "" ], [ "Yu", "Dongxiao", "" ] ]
We give efficient algorithms for the fundamental problems of Broadcast and Local Broadcast in dynamic wireless networks. We propose a general model of communication which captures and includes both fading models (like SINR) and graph-based models (such as quasi unit disc graphs, bounded-independence graphs, and protoco...
2104.04191
Jessica Yung
Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai
SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size
4 pages (10 pages including references and appendix), 10 figures. Accepted at the ICLR 2021 RobustML Workshop. arXiv admin note: text overlap with arXiv:2007.08558
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Before deploying machine learning models it is critical to assess their robustness. In the context of deep neural networks for image understanding, changing the object location, rotation and size may affect the predictions in non-trivial ways. In this work we perform a fine-grained analysis of robustness with respect...
[ { "created": "Fri, 9 Apr 2021 05:00:49 GMT", "version": "v1" } ]
2021-04-12
[ [ "Yung", "Jessica", "" ], [ "Romijnders", "Rob", "" ], [ "Kolesnikov", "Alexander", "" ], [ "Beyer", "Lucas", "" ], [ "Djolonga", "Josip", "" ], [ "Houlsby", "Neil", "" ], [ "Gelly", "Sylvain", "" ], [ ...
Before deploying machine learning models it is critical to assess their robustness. In the context of deep neural networks for image understanding, changing the object location, rotation and size may affect the predictions in non-trivial ways. In this work we perform a fine-grained analysis of robustness with respect t...
2104.05743
Pavlos Papadopoulos
Tom Titcombe, Adam J. Hall, Pavlos Papadopoulos, Daniele Romanini
Practical Defences Against Model Inversion Attacks for Split Neural Networks
ICLR 2021 Workshop on Distributed and Private Machine Learning (DPML 2021)
null
null
null
cs.LG cs.CR cs.DC
http://creativecommons.org/licenses/by/4.0/
We describe a threat model under which a split network-based federated learning system is susceptible to a model inversion attack by a malicious computational server. We demonstrate that the attack can be successfully performed with limited knowledge of the data distribution by the attacker. We propose a simple addit...
[ { "created": "Mon, 12 Apr 2021 18:12:17 GMT", "version": "v1" }, { "created": "Wed, 21 Apr 2021 11:01:25 GMT", "version": "v2" } ]
2021-04-22
[ [ "Titcombe", "Tom", "" ], [ "Hall", "Adam J.", "" ], [ "Papadopoulos", "Pavlos", "" ], [ "Romanini", "Daniele", "" ] ]
We describe a threat model under which a split network-based federated learning system is susceptible to a model inversion attack by a malicious computational server. We demonstrate that the attack can be successfully performed with limited knowledge of the data distribution by the attacker. We propose a simple additiv...
0912.3974
William Jackson
Martin Larrea, Dana Urribarri, Sergio Martig, Silvia Castro
Spherical Layout Implementation using Centroidal Voronoi Tessellations
null
Journal of Computing, Volume 1, Issue 1, pp 81-86, December 2009
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The 3D tree visualization faces multiple challenges: the election of an appropriate layout, the use of the interactions that make the data exploration easier and a metaphor that helps in the process of information understanding. A good combination of these elements will result in a visualization that effectively conv...
[ { "created": "Sun, 20 Dec 2009 03:53:20 GMT", "version": "v1" } ]
2009-12-22
[ [ "Larrea", "Martin", "" ], [ "Urribarri", "Dana", "" ], [ "Martig", "Sergio", "" ], [ "Castro", "Silvia", "" ] ]
The 3D tree visualization faces multiple challenges: the election of an appropriate layout, the use of the interactions that make the data exploration easier and a metaphor that helps in the process of information understanding. A good combination of these elements will result in a visualization that effectively convey...
2002.11078
Hao Guo
Hao Guo, Wanxin Li, Ehsan Meamari, Chien-Chung Shen, Mark Nejad
Attribute-based Multi-Signature and Encryption for EHR Management: A Blockchain-based Solution
This paper is accepted to the Short Paper track by 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC 2020)
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The global Electronic Health Record (EHR) market is growing dramatically and has already hit $31.5 billion in 2018. To safeguard the security of EHR data and privacy of patients, fine-grained information access and sharing mechanisms are essential for EHR management. This paper proposes a hybrid architecture of block...
[ { "created": "Tue, 25 Feb 2020 18:24:16 GMT", "version": "v1" } ]
2020-02-26
[ [ "Guo", "Hao", "" ], [ "Li", "Wanxin", "" ], [ "Meamari", "Ehsan", "" ], [ "Shen", "Chien-Chung", "" ], [ "Nejad", "Mark", "" ] ]
The global Electronic Health Record (EHR) market is growing dramatically and has already hit $31.5 billion in 2018. To safeguard the security of EHR data and privacy of patients, fine-grained information access and sharing mechanisms are essential for EHR management. This paper proposes a hybrid architecture of blockch...
2408.05750
Zitao Gao
Zhigang Tu, Zitao Gao, Zhengbo Zhang, Chunluan Zhou, Junsong Yuan, Bo Du
FADE: A Dataset for Detecting Falling Objects around Buildings in Video
11 pages, 10 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Falling objects from buildings can cause severe injuries to pedestrians due to the great impact force they exert. Although surveillance cameras are installed around some buildings, it is challenging for humans to capture such events in surveillance videos due to the small size and fast motion of falling objects, as w...
[ { "created": "Sun, 11 Aug 2024 11:43:56 GMT", "version": "v1" } ]
2024-08-13
[ [ "Tu", "Zhigang", "" ], [ "Gao", "Zitao", "" ], [ "Zhang", "Zhengbo", "" ], [ "Zhou", "Chunluan", "" ], [ "Yuan", "Junsong", "" ], [ "Du", "Bo", "" ] ]
Falling objects from buildings can cause severe injuries to pedestrians due to the great impact force they exert. Although surveillance cameras are installed around some buildings, it is challenging for humans to capture such events in surveillance videos due to the small size and fast motion of falling objects, as wel...
1108.2389
Anis Ismail
Anis Ismail, Abd El Salam Al Hajjar and Ziad Ismail
A New System Architecture for Pervasive Computing
15 pages, 4 figures
null
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present new system architecture, a distributed framework designed to support pervasive computing applications. We propose a new architecture consisting of a search engine and peripheral clients that addresses issues in scalability, data sharing, data transformation and inherent platform heterogeneity. Key features...
[ { "created": "Fri, 5 Aug 2011 18:19:51 GMT", "version": "v1" } ]
2011-08-12
[ [ "Ismail", "Anis", "" ], [ "Hajjar", "Abd El Salam Al", "" ], [ "Ismail", "Ziad", "" ] ]
We present new system architecture, a distributed framework designed to support pervasive computing applications. We propose a new architecture consisting of a search engine and peripheral clients that addresses issues in scalability, data sharing, data transformation and inherent platform heterogeneity. Key features o...
1705.05885
Benjamin Kunsberg
Daniel Niels Holtmann-Rice, Benjamin S. Kunsberg, Steven W. Zucker
What's In A Patch, I: Tensors, Differential Geometry and Statistical Shading Analysis
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a linear algebraic framework for the shape-from-shading problem, because tensors arise when scalar (e.g. image) and vector (e.g. surface normal) fields are differentiated multiple times. The work is in two parts. In this first part we investigate when image derivatives exhibit invariance to changing illumi...
[ { "created": "Tue, 16 May 2017 19:39:52 GMT", "version": "v1" } ]
2017-05-18
[ [ "Holtmann-Rice", "Daniel Niels", "" ], [ "Kunsberg", "Benjamin S.", "" ], [ "Zucker", "Steven W.", "" ] ]
We develop a linear algebraic framework for the shape-from-shading problem, because tensors arise when scalar (e.g. image) and vector (e.g. surface normal) fields are differentiated multiple times. The work is in two parts. In this first part we investigate when image derivatives exhibit invariance to changing illumina...
1511.01573
EPTCS
David Quick
Encoding !-tensors as !-graphs with neighbourhood orders
In Proceedings QPL 2015, arXiv:1511.01181
EPTCS 195, 2015, pp. 307-320
10.4204/EPTCS.195.23
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Diagrammatic reasoning using string diagrams provides an intuitive language for reasoning about morphisms in a symmetric monoidal category. To allow working with infinite families of string diagrams, !-graphs were introduced as a method to mark repeated structure inside a diagram. This led to !-graphs being implement...
[ { "created": "Thu, 5 Nov 2015 01:44:40 GMT", "version": "v1" } ]
2015-11-06
[ [ "Quick", "David", "" ] ]
Diagrammatic reasoning using string diagrams provides an intuitive language for reasoning about morphisms in a symmetric monoidal category. To allow working with infinite families of string diagrams, !-graphs were introduced as a method to mark repeated structure inside a diagram. This led to !-graphs being implemented...
2307.05494
Pengfei Li
Pengfei Li and Jianyi Yang and Adam Wierman and Shaolei Ren
Towards Environmentally Equitable AI via Geographical Load Balancing
Accepted by ACM e-Energy 2024
null
null
null
cs.AI cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fueled by the soaring popularity of large language and foundation models, the accelerated growth of artificial intelligence (AI) models' enormous environmental footprint has come under increased scrutiny. While many approaches have been proposed to make AI more energy-efficient and environmentally friendly, environme...
[ { "created": "Tue, 20 Jun 2023 17:13:33 GMT", "version": "v1" }, { "created": "Thu, 2 May 2024 06:10:54 GMT", "version": "v2" } ]
2024-05-03
[ [ "Li", "Pengfei", "" ], [ "Yang", "Jianyi", "" ], [ "Wierman", "Adam", "" ], [ "Ren", "Shaolei", "" ] ]
Fueled by the soaring popularity of large language and foundation models, the accelerated growth of artificial intelligence (AI) models' enormous environmental footprint has come under increased scrutiny. While many approaches have been proposed to make AI more energy-efficient and environmentally friendly, environment...
1605.03390
Mark Daniel Ward
Jeffrey Gaither and Mark Daniel Ward
Variance of the Internal Profile in Suffix Trees
19 pages, 0 figures
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The precise analysis of the variance of the profile of a suffix tree has been a longstanding open problem. We analyze three regimes of the asymptotic growth of the variance of the profile of a suffix tree built from a randomly generated binary string, in the nonuniform case. We utilize combinatorics on words, singula...
[ { "created": "Wed, 11 May 2016 11:47:59 GMT", "version": "v1" }, { "created": "Thu, 12 May 2016 22:54:52 GMT", "version": "v2" } ]
2016-05-16
[ [ "Gaither", "Jeffrey", "" ], [ "Ward", "Mark Daniel", "" ] ]
The precise analysis of the variance of the profile of a suffix tree has been a longstanding open problem. We analyze three regimes of the asymptotic growth of the variance of the profile of a suffix tree built from a randomly generated binary string, in the nonuniform case. We utilize combinatorics on words, singulari...
2306.12240
Arnaud Valence
Arnaud Valence
ICAR, a categorical framework to connect vulnerability, threat and asset managements
26 pages, 6 figures
null
null
null
cs.CR math.CT
http://creativecommons.org/licenses/by/4.0/
We present ICAR, a mathematical framework derived from category theory for representing cybersecurity NIST and MITRE's ontologies. Designed for cybersecurity, ICAR is a category whose objects are cybersecurity knowledge (weakness, vulnerability, impacted product, attack technique, etc.) and whose morphisms are relati...
[ { "created": "Wed, 21 Jun 2023 12:59:29 GMT", "version": "v1" } ]
2023-06-22
[ [ "Valence", "Arnaud", "" ] ]
We present ICAR, a mathematical framework derived from category theory for representing cybersecurity NIST and MITRE's ontologies. Designed for cybersecurity, ICAR is a category whose objects are cybersecurity knowledge (weakness, vulnerability, impacted product, attack technique, etc.) and whose morphisms are relation...
2103.13689
Shunquan Tan
Xianbo Mo and Shunquan Tan and Bin Li and Jiwu Huang
MCTSteg: A Monte Carlo Tree Search-based Reinforcement Learning Framework for Universal Non-additive Steganography
accepted by TIFS
null
10.1109/TIFS.2021.3104140
null
cs.MM cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent research has shown that non-additive image steganographic frameworks effectively improve security performance through adjusting distortion distribution. However, as far as we know, all of the existing non-additive proposals are based on handcrafted policies, and can only be applied to a specific image domain, ...
[ { "created": "Thu, 25 Mar 2021 09:12:08 GMT", "version": "v1" }, { "created": "Tue, 10 Aug 2021 07:01:06 GMT", "version": "v2" } ]
2021-08-11
[ [ "Mo", "Xianbo", "" ], [ "Tan", "Shunquan", "" ], [ "Li", "Bin", "" ], [ "Huang", "Jiwu", "" ] ]
Recent research has shown that non-additive image steganographic frameworks effectively improve security performance through adjusting distortion distribution. However, as far as we know, all of the existing non-additive proposals are based on handcrafted policies, and can only be applied to a specific image domain, wh...
2011.07577
Harshit Rampal
Dhruv Vashisht, Harshit Rampal, Haiguang Liao, Yang Lu, Devika Shanbhag, Elias Fallon, Levent Burak Kara
Placement in Integrated Circuits using Cyclic Reinforcement Learning and Simulated Annealing
null
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Physical design and production of Integrated Circuits (IC) is becoming increasingly more challenging as the sophistication in IC technology is steadily increasing. Placement has been one of the most critical steps in IC physical design. Through decades of research, partition-based, analytical-based and annealing-base...
[ { "created": "Sun, 15 Nov 2020 16:48:56 GMT", "version": "v1" } ]
2020-11-17
[ [ "Vashisht", "Dhruv", "" ], [ "Rampal", "Harshit", "" ], [ "Liao", "Haiguang", "" ], [ "Lu", "Yang", "" ], [ "Shanbhag", "Devika", "" ], [ "Fallon", "Elias", "" ], [ "Kara", "Levent Burak", "" ] ]
Physical design and production of Integrated Circuits (IC) is becoming increasingly more challenging as the sophistication in IC technology is steadily increasing. Placement has been one of the most critical steps in IC physical design. Through decades of research, partition-based, analytical-based and annealing-based ...
1712.06070
Andres Felipe Cruz Salinas
Andres Felipe Cruz Salinas and Jonatan Gomez Perdomo
Self-adaptation of Genetic Operators Through Genetic Programming Techniques
Presented in GECCO 2017
null
10.1145/3071178.3071214
null
cs.NE
http://creativecommons.org/publicdomain/zero/1.0/
Here we propose an evolutionary algorithm that self modifies its operators at the same time that candidate solutions are evolved. This tackles convergence and lack of diversity issues, leading to better solutions. Operators are represented as trees and are evolved using genetic programming (GP) techniques. The propos...
[ { "created": "Sun, 17 Dec 2017 07:53:36 GMT", "version": "v1" } ]
2017-12-19
[ [ "Salinas", "Andres Felipe Cruz", "" ], [ "Perdomo", "Jonatan Gomez", "" ] ]
Here we propose an evolutionary algorithm that self modifies its operators at the same time that candidate solutions are evolved. This tackles convergence and lack of diversity issues, leading to better solutions. Operators are represented as trees and are evolved using genetic programming (GP) techniques. The proposed...
2107.00189
Xiangyu Xi
Xiangyu Xi, Wei Ye, Shikun Zhang, Quanxiu Wang, Huixing Jiang, Wei Wu
Capturing Event Argument Interaction via A Bi-Directional Entity-Level Recurrent Decoder
null
ACL-IJCNLP 2021
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Capturing interactions among event arguments is an essential step towards robust event argument extraction (EAE). However, existing efforts in this direction suffer from two limitations: 1) The argument role type information of contextual entities is mainly utilized as training signals, ignoring the potential merits ...
[ { "created": "Thu, 1 Jul 2021 02:55:12 GMT", "version": "v1" } ]
2021-07-02
[ [ "Xi", "Xiangyu", "" ], [ "Ye", "Wei", "" ], [ "Zhang", "Shikun", "" ], [ "Wang", "Quanxiu", "" ], [ "Jiang", "Huixing", "" ], [ "Wu", "Wei", "" ] ]
Capturing interactions among event arguments is an essential step towards robust event argument extraction (EAE). However, existing efforts in this direction suffer from two limitations: 1) The argument role type information of contextual entities is mainly utilized as training signals, ignoring the potential merits of...
2309.01103
Wei Wei
Wei Wei, Lianghao Xia, Chao Huang
Multi-Relational Contrastive Learning for Recommendation
This paper has been published as a full paper at RecSys 2023
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Personalized recommender systems play a crucial role in capturing users' evolving preferences over time to provide accurate and effective recommendations on various online platforms. However, many recommendation models rely on a single type of behavior learning, which limits their ability to represent the complex rel...
[ { "created": "Sun, 3 Sep 2023 06:56:45 GMT", "version": "v1" }, { "created": "Sat, 23 Sep 2023 17:10:13 GMT", "version": "v2" }, { "created": "Fri, 20 Oct 2023 05:10:14 GMT", "version": "v3" } ]
2023-10-23
[ [ "Wei", "Wei", "" ], [ "Xia", "Lianghao", "" ], [ "Huang", "Chao", "" ] ]
Personalized recommender systems play a crucial role in capturing users' evolving preferences over time to provide accurate and effective recommendations on various online platforms. However, many recommendation models rely on a single type of behavior learning, which limits their ability to represent the complex relat...
2007.06141
Wenying Wu
Wenying Wu, Pavlos Protopapas, Zheng Yang, Panagiotis Michalatos
Gender Classification and Bias Mitigation in Facial Images
9 pages
WebSci (2020) 106-114
10.1145/3394231
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gender classification algorithms have important applications in many domains today such as demographic research, law enforcement, as well as human-computer interaction. Recent research showed that algorithms trained on biased benchmark databases could result in algorithmic bias. However, to date, little research has ...
[ { "created": "Mon, 13 Jul 2020 01:09:06 GMT", "version": "v1" } ]
2020-07-14
[ [ "Wu", "Wenying", "" ], [ "Protopapas", "Pavlos", "" ], [ "Yang", "Zheng", "" ], [ "Michalatos", "Panagiotis", "" ] ]
Gender classification algorithms have important applications in many domains today such as demographic research, law enforcement, as well as human-computer interaction. Recent research showed that algorithms trained on biased benchmark databases could result in algorithmic bias. However, to date, little research has be...
2205.03398
Ulrike Kuhl
Ulrike Kuhl and Andr\'e Artelt and Barbara Hammer
Let's Go to the Alien Zoo: Introducing an Experimental Framework to Study Usability of Counterfactual Explanations for Machine Learning
We provide the entire code, together with the underlying models and user data: https://github.com/ukuhl/IntroAlienZoo
Front.Comput.Sci. (2023), Sec. Theoretical Computer Science, Volume 5
10.3389/fcomp.2023.1087929
null
cs.HC cs.LG
http://creativecommons.org/licenses/by/4.0/
To foster usefulness and accountability of machine learning (ML), it is essential to explain a model's decisions in addition to evaluating its performance. Accordingly, the field of explainable artificial intelligence (XAI) has resurfaced as a topic of active research, offering approaches to address the "how" and "wh...
[ { "created": "Fri, 6 May 2022 17:57:05 GMT", "version": "v1" } ]
2023-03-24
[ [ "Kuhl", "Ulrike", "" ], [ "Artelt", "André", "" ], [ "Hammer", "Barbara", "" ] ]
To foster usefulness and accountability of machine learning (ML), it is essential to explain a model's decisions in addition to evaluating its performance. Accordingly, the field of explainable artificial intelligence (XAI) has resurfaced as a topic of active research, offering approaches to address the "how" and "why"...
2205.13481
Vincent Jeanselme
Vincent Jeanselme, Glen Martin, Niels Peek, Matthew Sperrin, Brian Tom and Jessica Barrett
DeepJoint: Robust Survival Modelling Under Clinical Presence Shift
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Observational data in medicine arise as a result of the complex interaction between patients and the healthcare system. The sampling process is often highly irregular and itself constitutes an informative process. When using such data to develop prediction models, this phenomenon is often ignored, leading to sub-opti...
[ { "created": "Thu, 26 May 2022 16:42:38 GMT", "version": "v1" } ]
2022-05-27
[ [ "Jeanselme", "Vincent", "" ], [ "Martin", "Glen", "" ], [ "Peek", "Niels", "" ], [ "Sperrin", "Matthew", "" ], [ "Tom", "Brian", "" ], [ "Barrett", "Jessica", "" ] ]
Observational data in medicine arise as a result of the complex interaction between patients and the healthcare system. The sampling process is often highly irregular and itself constitutes an informative process. When using such data to develop prediction models, this phenomenon is often ignored, leading to sub-optima...
2112.00842
Sebastian Perez-Salazar
Sebastian Perez-Salazar, Mohit Singh, Alejandro Toriello
Robust Online Selection with Uncertain Offer Acceptance
null
null
null
null
cs.GT math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Online advertising has motivated interest in online selection problems. Displaying ads to the right users benefits both the platform (e.g., via pay-per-click) and the advertisers (by increasing their reach). In practice, not all users click on displayed ads, while the platform's algorithm may miss the users most disp...
[ { "created": "Wed, 1 Dec 2021 21:41:13 GMT", "version": "v1" }, { "created": "Thu, 15 Aug 2024 14:59:42 GMT", "version": "v2" } ]
2024-08-16
[ [ "Perez-Salazar", "Sebastian", "" ], [ "Singh", "Mohit", "" ], [ "Toriello", "Alejandro", "" ] ]
Online advertising has motivated interest in online selection problems. Displaying ads to the right users benefits both the platform (e.g., via pay-per-click) and the advertisers (by increasing their reach). In practice, not all users click on displayed ads, while the platform's algorithm may miss the users most dispos...
2403.12935
Luis Diaz-Garcia
Efrain Torres-Lomas, Jimena Lado-Jimena, Guillermo Garcia-Zamora, Luis Diaz-Garcia
Segment Anything for comprehensive analysis of grapevine cluster architecture and berry properties
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Grape cluster architecture and compactness are complex traits influencing disease susceptibility, fruit quality, and yield. Evaluation methods for these traits include visual scoring, manual methodologies, and computer vision, with the latter being the most scalable approach. Most of the existing computer vision appr...
[ { "created": "Tue, 19 Mar 2024 17:37:18 GMT", "version": "v1" } ]
2024-03-20
[ [ "Torres-Lomas", "Efrain", "" ], [ "Lado-Jimena", "Jimena", "" ], [ "Garcia-Zamora", "Guillermo", "" ], [ "Diaz-Garcia", "Luis", "" ] ]
Grape cluster architecture and compactness are complex traits influencing disease susceptibility, fruit quality, and yield. Evaluation methods for these traits include visual scoring, manual methodologies, and computer vision, with the latter being the most scalable approach. Most of the existing computer vision approa...
1511.04629
Tomaso Erseghe
Tomaso Erseghe
Coding in the Finite-Blocklength Regime: Bounds based on Laplace Integrals and their Asymptotic Approximations
29 pages, 10 figures. Submitted to IEEE Trans. on Information Theory. Matlab code available from http://dgt.dei.unipd.it section Download->Finite Blocklength Regime
null
10.1109/TIT.2016.2616900
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we provide new compact integral expressions and associated simple asymptotic approximations for converse and achievability bounds in the finite blocklength regime. The chosen converse and random coding union bounds were taken from the recent work of Polyanskyi-Poor-Verdu, and are investigated under para...
[ { "created": "Sat, 14 Nov 2015 22:14:30 GMT", "version": "v1" }, { "created": "Wed, 15 Jun 2016 13:12:37 GMT", "version": "v2" } ]
2016-10-25
[ [ "Erseghe", "Tomaso", "" ] ]
In this paper we provide new compact integral expressions and associated simple asymptotic approximations for converse and achievability bounds in the finite blocklength regime. The chosen converse and random coding union bounds were taken from the recent work of Polyanskyi-Poor-Verdu, and are investigated under parall...
1908.02781
Amir Mosavi Prof
Amir Mosavi, Pinar Ozturk, Kwok-wing Chau
Flood Prediction Using Machine Learning Models: Literature Review
74 pages, 10 figures, 6 tables
Water 2018, 10, 1536
10.3390/w10111536
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Floods are among the most destructive natural disasters, which are highly complex to model. The research on the advancement of flood prediction models contributed to risk reduction, policy suggestion, minimization of the loss of human life, and reduction the property damage associated with floods. To mimic the comple...
[ { "created": "Wed, 7 Aug 2019 18:05:45 GMT", "version": "v1" } ]
2020-08-10
[ [ "Mosavi", "Amir", "" ], [ "Ozturk", "Pinar", "" ], [ "Chau", "Kwok-wing", "" ] ]
Floods are among the most destructive natural disasters, which are highly complex to model. The research on the advancement of flood prediction models contributed to risk reduction, policy suggestion, minimization of the loss of human life, and reduction the property damage associated with floods. To mimic the complex ...
2305.09924
Hao Zheng
Hao Zheng, Jinbao Wang, Xiantong Zhen, Hong Chen, Jingkuan Song, Feng Zheng
CageViT: Convolutional Activation Guided Efficient Vision Transformer
9 pages, 3 figures, NeurIPS conference
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, Transformers have emerged as the go-to architecture for both vision and language modeling tasks, but their computational efficiency is limited by the length of the input sequence. To address this, several efficient variants of Transformers have been proposed to accelerate computation or reduce memory consum...
[ { "created": "Wed, 17 May 2023 03:19:18 GMT", "version": "v1" } ]
2023-05-18
[ [ "Zheng", "Hao", "" ], [ "Wang", "Jinbao", "" ], [ "Zhen", "Xiantong", "" ], [ "Chen", "Hong", "" ], [ "Song", "Jingkuan", "" ], [ "Zheng", "Feng", "" ] ]
Recently, Transformers have emerged as the go-to architecture for both vision and language modeling tasks, but their computational efficiency is limited by the length of the input sequence. To address this, several efficient variants of Transformers have been proposed to accelerate computation or reduce memory consumpt...
1903.08481
Jonathan Williams
Jonathan Williams, Carola-Bibiane Sch\"onlieb, Tom Swinfield, Juheon Lee, Xiaohao Cai, Lan Qie, David A. Coomes
Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC)
null
null
10.1109/TGRS.2019.2940146
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Developing a robust algorithm for automatic individual tree crown (ITC) detection from laser scanning datasets is important for tracking the responses of trees to anthropogenic change. Such approaches allow the size, growth and mortality of individual trees to be measured, enabling forest carbon stocks and dynamics t...
[ { "created": "Wed, 20 Mar 2019 12:35:17 GMT", "version": "v1" } ]
2019-10-04
[ [ "Williams", "Jonathan", "" ], [ "Schönlieb", "Carola-Bibiane", "" ], [ "Swinfield", "Tom", "" ], [ "Lee", "Juheon", "" ], [ "Cai", "Xiaohao", "" ], [ "Qie", "Lan", "" ], [ "Coomes", "David A.", "" ] ]
Developing a robust algorithm for automatic individual tree crown (ITC) detection from laser scanning datasets is important for tracking the responses of trees to anthropogenic change. Such approaches allow the size, growth and mortality of individual trees to be measured, enabling forest carbon stocks and dynamics to ...
1410.1729
Andrey Shchurov
Andrey A. Shchurov
A Formal Model of Distributed Systems For Test Generation Missions
6 pages, 9 figures
International Journal of Computer Trends and Technology (IJCTT) V15(2):128-133, September 2014
10.14445/22312803/IJCTT-V15P128
null
cs.SE cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nowadays, deployment of distributed systems sets high requirements for procedures and tools for the complex testing of these systems - virtualization and cloud technologies make another level of system complexity. As a possible solution, it is necessary to determine a formal list of control objectives - checklists. T...
[ { "created": "Mon, 6 Oct 2014 10:57:38 GMT", "version": "v1" } ]
2014-10-08
[ [ "Shchurov", "Andrey A.", "" ] ]
Nowadays, deployment of distributed systems sets high requirements for procedures and tools for the complex testing of these systems - virtualization and cloud technologies make another level of system complexity. As a possible solution, it is necessary to determine a formal list of control objectives - checklists. The...
1402.3718
Ying Long
Ying Long, Kang Wu, Qizhi Mao
Simulating urban expansion in the parcel level for all Chinese cities
23 pages, 8 figures
null
null
null
cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large-scale models are generally associated with big modelling units in space, like counties or super grids (several to dozens km2). Few applied urban models can pursue large-scale extent with fine-level units simultaneously due to data availability and computation load. The framework of automatic identification and ...
[ { "created": "Sat, 15 Feb 2014 19:57:07 GMT", "version": "v1" } ]
2014-02-18
[ [ "Long", "Ying", "" ], [ "Wu", "Kang", "" ], [ "Mao", "Qizhi", "" ] ]
Large-scale models are generally associated with big modelling units in space, like counties or super grids (several to dozens km2). Few applied urban models can pursue large-scale extent with fine-level units simultaneously due to data availability and computation load. The framework of automatic identification and ch...
2006.08327
Raphael Kramer
Raphael Kramer and Arthur Kramer
Exact and heuristic methods for the discrete parallel machine scheduling location problem
25 pages, 5 figures, 7 tables
null
null
null
cs.AI math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The discrete parallel machine makespan scheduling location (ScheLoc) problem is an integrated combinatorial optimization problem that combines facility location and job scheduling. The problem consists in choosing the locations of $p$ machines among a finite set of candidates and scheduling a set of jobs on these mac...
[ { "created": "Tue, 9 Jun 2020 00:10:18 GMT", "version": "v1" } ]
2020-06-16
[ [ "Kramer", "Raphael", "" ], [ "Kramer", "Arthur", "" ] ]
The discrete parallel machine makespan scheduling location (ScheLoc) problem is an integrated combinatorial optimization problem that combines facility location and job scheduling. The problem consists in choosing the locations of $p$ machines among a finite set of candidates and scheduling a set of jobs on these machi...
1711.11427
Saugata Ghose
Yu Cai, Saugata Ghose, Erich F. Haratsch, Yixin Luo, Onur Mutlu
Errors in Flash-Memory-Based Solid-State Drives: Analysis, Mitigation, and Recovery
arXiv admin note: substantial text overlap with arXiv:1706.08642
null
null
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
NAND flash memory is ubiquitous in everyday life today because its capacity has continuously increased and cost has continuously decreased over decades. This positive growth is a result of two key trends: (1) effective process technology scaling; and (2) multi-level (e.g., MLC, TLC) cell data coding. Unfortunately, t...
[ { "created": "Tue, 28 Nov 2017 19:54:09 GMT", "version": "v1" }, { "created": "Fri, 5 Jan 2018 15:17:52 GMT", "version": "v2" } ]
2018-01-08
[ [ "Cai", "Yu", "" ], [ "Ghose", "Saugata", "" ], [ "Haratsch", "Erich F.", "" ], [ "Luo", "Yixin", "" ], [ "Mutlu", "Onur", "" ] ]
NAND flash memory is ubiquitous in everyday life today because its capacity has continuously increased and cost has continuously decreased over decades. This positive growth is a result of two key trends: (1) effective process technology scaling; and (2) multi-level (e.g., MLC, TLC) cell data coding. Unfortunately, the...
1901.09165
Bo Bai
Kai Lei, Meng Qin, Bo Bai, Gong Zhang, Min Yang
GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks
to appear in IEEE Infocom 2019
null
null
null
cs.SI cs.LG cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we generally formulate the dynamics prediction problem of various network systems (e.g., the prediction of mobility, traffic and topology) as the temporal link prediction task. Different from conventional techniques of temporal link prediction that ignore the potential non-linear characteristics and th...
[ { "created": "Sat, 26 Jan 2019 05:42:05 GMT", "version": "v1" } ]
2019-01-29
[ [ "Lei", "Kai", "" ], [ "Qin", "Meng", "" ], [ "Bai", "Bo", "" ], [ "Zhang", "Gong", "" ], [ "Yang", "Min", "" ] ]
In this paper, we generally formulate the dynamics prediction problem of various network systems (e.g., the prediction of mobility, traffic and topology) as the temporal link prediction task. Different from conventional techniques of temporal link prediction that ignore the potential non-linear characteristics and the ...
1904.06850
EPTCS
Carlos Olarte (UFRN), Valeria de Paiva (Nuance Communications), Elaine Pimentel (UFRN), Giselle Reis (CMU-Qatar)
The ILLTP Library for Intuitionistic Linear Logic
In Proceedings Linearity-TLLA 2018, arXiv:1904.06159
EPTCS 292, 2019, pp. 118-132
10.4204/EPTCS.292.7
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Benchmarking automated theorem proving (ATP) systems using standardized problem sets is a well-established method for measuring their performance. However, the availability of such libraries for non-classical logics is very limited. In this work we propose a library for benchmarking Girard's (propositional) intuition...
[ { "created": "Mon, 15 Apr 2019 05:17:35 GMT", "version": "v1" } ]
2019-04-16
[ [ "Olarte", "Carlos", "", "UFRN" ], [ "de Paiva", "Valeria", "", "Nuance Communications" ], [ "Pimentel", "Elaine", "", "UFRN" ], [ "Reis", "Giselle", "", "CMU-Qatar" ] ]
Benchmarking automated theorem proving (ATP) systems using standardized problem sets is a well-established method for measuring their performance. However, the availability of such libraries for non-classical logics is very limited. In this work we propose a library for benchmarking Girard's (propositional) intuitionis...
2403.19729
Pablo Fondo-Ferreiro
David Candal-Ventureira, Francisco Javier Gonz\'alez-Casta\~no, Felipe Gil-Casti\~neira, Pablo Fondo-Ferreiro
Is the edge really necessary for drone computing offloading? An experimental assessment in carrier-grade 5G operator networks
Article published in Software: Practice and Experience
Software: Practice and Experience, vol. 53, no. 3, pp. 579-599, March 2023
10.1002/spe.3161
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
In this article, we evaluate the first experience of computation offloading from drones to real fifth-generation (5G) operator systems, including commercial and private carrier-grade 5G networks. A follow-me drone service was implemented as a representative testbed of remote video analytics. In this application, an i...
[ { "created": "Thu, 28 Mar 2024 12:26:10 GMT", "version": "v1" } ]
2024-04-01
[ [ "Candal-Ventureira", "David", "" ], [ "González-Castaño", "Francisco Javier", "" ], [ "Gil-Castiñeira", "Felipe", "" ], [ "Fondo-Ferreiro", "Pablo", "" ] ]
In this article, we evaluate the first experience of computation offloading from drones to real fifth-generation (5G) operator systems, including commercial and private carrier-grade 5G networks. A follow-me drone service was implemented as a representative testbed of remote video analytics. In this application, an ima...
1601.07352
Nicolas Nicolaou
Nicolas Nicolaou and Antonio Fern\'andez Anta and Chryssis Georgiou
CoVer-ability: Consistent Versioning for Concurrent Objects
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An object type characterizes the domain space and the operations that can be invoked on an object of that type. In this paper we introduce a new property for concurrent objects, we call coverability, that aims to provide precise guarantees on the consistent evolution of an object. This new property is suitable for a ...
[ { "created": "Wed, 27 Jan 2016 13:09:30 GMT", "version": "v1" }, { "created": "Tue, 16 Feb 2016 13:27:39 GMT", "version": "v2" }, { "created": "Fri, 11 Mar 2016 18:35:55 GMT", "version": "v3" } ]
2016-03-14
[ [ "Nicolaou", "Nicolas", "" ], [ "Anta", "Antonio Fernández", "" ], [ "Georgiou", "Chryssis", "" ] ]
An object type characterizes the domain space and the operations that can be invoked on an object of that type. In this paper we introduce a new property for concurrent objects, we call coverability, that aims to provide precise guarantees on the consistent evolution of an object. This new property is suitable for a va...
2205.14315
Zhe Zhang
Kan Xie, Zhe Zhang, Bo Li, Jiawen Kang, Dusit Niyato, Shengli Xie, Yi Wu
Efficient Federated Learning with Spike Neural Networks for Traffic Sign Recognition
Submitted by IEEE Transactions on Vehicular Technology
null
null
null
cs.LG eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the gradual popularization of self-driving, it is becoming increasingly important for vehicles to smartly make the right driving decisions and autonomously obey traffic rules by correctly recognizing traffic signs. However, for machine learning-based traffic sign recognition on the Internet of Vehicles (IoV), a ...
[ { "created": "Sat, 28 May 2022 03:11:48 GMT", "version": "v1" } ]
2022-06-01
[ [ "Xie", "Kan", "" ], [ "Zhang", "Zhe", "" ], [ "Li", "Bo", "" ], [ "Kang", "Jiawen", "" ], [ "Niyato", "Dusit", "" ], [ "Xie", "Shengli", "" ], [ "Wu", "Yi", "" ] ]
With the gradual popularization of self-driving, it is becoming increasingly important for vehicles to smartly make the right driving decisions and autonomously obey traffic rules by correctly recognizing traffic signs. However, for machine learning-based traffic sign recognition on the Internet of Vehicles (IoV), a la...
1606.02503
Po-Yen Chen
Po-Yen Chen and Chorng-Shyong Ong
The Development Strategy of IT Capability: A Contingency Perspective
ISBN# 978-0-646-95337-3 Presented at the Australasian Conference on Information Systems 2015 (arXiv:1605.01032)
null
null
ACIS/2015/174
cs.CY
http://creativecommons.org/licenses/by-nc-sa/4.0/
This study proposes a conceptual model to link IT capabilities, industry types, and value implications. We attempt to use a contingency analysis to theorize that which types of IT capabilities (e.g., externally-focused, internally-focused, and aggregate IT capability) should a firm develop and then what benefits (e.g...
[ { "created": "Wed, 8 Jun 2016 10:51:35 GMT", "version": "v1" } ]
2016-06-09
[ [ "Chen", "Po-Yen", "" ], [ "Ong", "Chorng-Shyong", "" ] ]
This study proposes a conceptual model to link IT capabilities, industry types, and value implications. We attempt to use a contingency analysis to theorize that which types of IT capabilities (e.g., externally-focused, internally-focused, and aggregate IT capability) should a firm develop and then what benefits (e.g.,...
2208.02892
Julian Kates-Harbeck
Julian Kates-Harbeck, Martin A. Nowak
Trust based attachment
null
null
10.1371/journal.pone.0288142
null
cs.SI physics.soc-ph
http://creativecommons.org/licenses/by/4.0/
In social systems subject to indirect reciprocity, a positive reputation is key for increasing one's likelihood of future positive interactions. The flow of gossip can amplify the impact of a person's actions on their reputation depending on how widely it spreads across the social network, which leads to a percolatio...
[ { "created": "Thu, 4 Aug 2022 21:27:13 GMT", "version": "v1" }, { "created": "Tue, 29 Aug 2023 07:03:00 GMT", "version": "v2" } ]
2023-08-30
[ [ "Kates-Harbeck", "Julian", "" ], [ "Nowak", "Martin A.", "" ] ]
In social systems subject to indirect reciprocity, a positive reputation is key for increasing one's likelihood of future positive interactions. The flow of gossip can amplify the impact of a person's actions on their reputation depending on how widely it spreads across the social network, which leads to a percolation ...
2103.09882
Yosi Keller
Shakediel Hiba and Yosi Keller
Hierarchical Attention-based Age Estimation and Bias Estimation
11 pages, 7 figures
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In this work we propose a novel deep-learning approach for age estimation based on face images. We first introduce a dual image augmentation-aggregation approach based on attention. This allows the network to jointly utilize multiple face image augmentations whose embeddings are aggregated by a Transformer-Encoder. T...
[ { "created": "Wed, 17 Mar 2021 19:41:34 GMT", "version": "v1" }, { "created": "Wed, 27 Sep 2023 21:26:08 GMT", "version": "v2" } ]
2023-09-29
[ [ "Hiba", "Shakediel", "" ], [ "Keller", "Yosi", "" ] ]
In this work we propose a novel deep-learning approach for age estimation based on face images. We first introduce a dual image augmentation-aggregation approach based on attention. This allows the network to jointly utilize multiple face image augmentations whose embeddings are aggregated by a Transformer-Encoder. The...
2207.00708
Ziwen Han
Ziwen Han, Evgeniya Gorobets, Pan Chen
Parameter efficient dendritic-tree neurons outperform perceptrons
null
null
null
null
cs.NE cs.LG
http://creativecommons.org/licenses/by/4.0/
Biological neurons are more powerful than artificial perceptrons, in part due to complex dendritic input computations. Inspired to empower the perceptron with biologically inspired features, we explore the effect of adding and tuning input branching factors along with input dropout. This allows for parameter efficien...
[ { "created": "Sat, 2 Jul 2022 01:22:39 GMT", "version": "v1" } ]
2022-07-05
[ [ "Han", "Ziwen", "" ], [ "Gorobets", "Evgeniya", "" ], [ "Chen", "Pan", "" ] ]
Biological neurons are more powerful than artificial perceptrons, in part due to complex dendritic input computations. Inspired to empower the perceptron with biologically inspired features, we explore the effect of adding and tuning input branching factors along with input dropout. This allows for parameter efficient ...
2212.03669
Iztok Fister
Iztok Fister Jr. and Du\v{s}an Fister and Iztok Fister and Vili Podgorelec and Sancho Salcedo-Sanz
Time series numerical association rule mining variants in smart agriculture
null
null
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Numerical association rule mining offers a very efficient way of mining association rules, where algorithms can operate directly with categorical and numerical attributes. These methods are suitable for mining different transaction databases, where data are entered sequentially. However, little attention has been pai...
[ { "created": "Wed, 7 Dec 2022 14:35:23 GMT", "version": "v1" } ]
2022-12-08
[ [ "Fister", "Iztok", "Jr." ], [ "Fister", "Dušan", "" ], [ "Fister", "Iztok", "" ], [ "Podgorelec", "Vili", "" ], [ "Salcedo-Sanz", "Sancho", "" ] ]
Numerical association rule mining offers a very efficient way of mining association rules, where algorithms can operate directly with categorical and numerical attributes. These methods are suitable for mining different transaction databases, where data are entered sequentially. However, little attention has been paid ...
1609.06141
Martin Danelljan
Martin Danelljan, Gustav H\"ager, Fahad Shahbaz Khan, Michael Felsberg
Discriminative Scale Space Tracking
To appear in TPAMI. This is the journal extension of the VOT2014-winning DSST tracking method
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurate scale estimation of a target is a challenging research problem in visual object tracking. Most state-of-the-art methods employ an exhaustive scale search to estimate the target size. The exhaustive search strategy is computationally expensive and struggles when encountered with large scale variations. This p...
[ { "created": "Tue, 20 Sep 2016 12:57:08 GMT", "version": "v1" } ]
2016-09-21
[ [ "Danelljan", "Martin", "" ], [ "Häger", "Gustav", "" ], [ "Khan", "Fahad Shahbaz", "" ], [ "Felsberg", "Michael", "" ] ]
Accurate scale estimation of a target is a challenging research problem in visual object tracking. Most state-of-the-art methods employ an exhaustive scale search to estimate the target size. The exhaustive search strategy is computationally expensive and struggles when encountered with large scale variations. This pap...