Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
1608.05221	Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation	Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in moder power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	59,949
2311.01894	Simulation of acquisition shifts in T2 Flair MR images to stress test AI segmentation networks	Purpose: To provide a simulation framework for routine neuroimaging test data, which allows for "stress testing" of deep segmentation networks against acquisition shifts that commonly occur in clinical practice for T2 weighted (T2w) fluid attenuated inversion recovery (FLAIR) Magnetic Resonance Imaging (MRI) protocols....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	405,218
2010.07785	Response Selection for Multi-Party Conversations with Dynamic Topic Tracking	While participants in a multi-party multi-turn conversation simultaneously engage in multiple conversation topics, existing response selection methods are developed mainly focusing on a two-party single-conversation scenario. Hence, the prolongation and transition of conversation topics are ignored by current methods. ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	200,940
2103.12770	Distributed Visual-Inertial Cooperative Localization	In this paper we present a consistent and distributed state estimator for multi-robot cooperative localization (CL) which efficiently fuses environmental features and loop-closure constraints across time and robots. In particular, we leverage covariance intersection (CI) to allow each robot to only estimate its own sta...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	226,280
1303.7310	Exploring the Role of Logically Related Non-Question Phrases for Answering Why-Questions	In this paper, we show that certain phrases although not present in a given question/query, play a very important role in answering the question. Exploring the role of such phrases in answering questions not only reduces the dependency on matching question phrases for extracting answers, but also improves the quality o...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	23,341
1409.8053	Medical diagnosis as pattern recognition in a framework of information compression by multiple alignment, unification and search	This paper describes a novel approach to medical diagnosis based on the SP theory of computing and cognition. The main attractions of this approach are: a format for representing diseases that is simple and intuitive; an ability to cope with errors and uncertainties in diagnostic information; the simplicity of storing ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	36,382
2409.08963	Safeguarding Decentralized Social Media: LLM Agents for Automating Community Rule Compliance	Ensuring content compliance with community guidelines is crucial for maintaining healthy online social environments. However, traditional human-based compliance checking struggles with scaling due to the increasing volume of user-generated content and a limited number of moderators. Recent advancements in Natural Langu...	true	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	488,121
2302.02025	Self-Supervised Transformer Architecture for Change Detection in Radio Access Networks	Radio Access Networks (RANs) for telecommunications represent large agglomerations of interconnected hardware consisting of hundreds of thousands of transmitting devices (cells). Such networks undergo frequent and often heterogeneous changes caused by network operators, who are seeking to tune their system parameters f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,822
2304.06103	$E(3) \times SO(3)$-Equivariant Networks for Spherical Deconvolution in Diffusion MRI	We present Roto-Translation Equivariant Spherical Deconvolution (RT-ESD), an $E(3)\times SO(3)$ equivariant framework for sparse deconvolution of volumes where each voxel contains a spherical signal. Such 6D data naturally arises in diffusion MRI (dMRI), a medical imaging modality widely used to measure microstructure ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,851
1904.09445	Performance and Resilience of Cyber-Physical Control Systems with Reactive Attack Mitigation	This paper studies the performance and resilience of a linear cyber-physical control system (CPCS) with attack detection and reactive attack mitigation in the context of power grids. It addresses the problem of deriving an optimal sequence of false data injection attacks that maximizes the state estimation error of the...	false	false	false	false	false	false	false	false	false	true	true	false	true	false	false	false	false	false	128,381
2404.13685	Second-Order Identification Capacity of AWGN Channels	In this paper, we establish the second-order randomized identification capacity (RID capacity) of the Additive White Gaussian Noise Channel (AWGNC). On the one hand, we obtain a refined version of Hayashi's theorem to prove the achievability part. On the other, we investigate the relationship between identification and...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	448,400
2406.18514	Addressing intra-area oscillations and frequency stability after DC segmentation of a large AC power system	In the last decades, various events have shown that electromechanical oscillations are a major concern for large interconnected Alternating Current (AC) power systems. Segmentation of AC power systems with High Voltage Direct Current (HVDC) systems (DC segmentation, for short) is a method that consists in turning large...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	468,032
2012.02046	Neural Prototype Trees for Interpretable Fine-grained Image Recognition	Prototype-based methods use interpretable representations to address the black-box nature of deep learning models, in contrast to post-hoc explanation methods that only approximate such models. We propose the Neural Prototype Tree (ProtoTree), an intrinsically interpretable deep learning method for fine-grained image r...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	209,633
2501.06192	A Computational Model of Learning and Memory Using Structurally Dynamic Cellular Automata	In the fields of computation and neuroscience, much is still unknown about the underlying computations that enable key cognitive functions including learning, memory, abstraction and behavior. This paper proposes a mathematical and computational model of learning and memory based on a small set of bio-plausible functio...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	523,869
2309.12591	Auditing the Compliance and Enforcement of Twitter's Advertising Policy	Online platforms have enacted various policies to maintain a safe and trustworthy advertising environment. However, the extent to which these policies are adhered to and enforced remains a subject of interest and concern. In this work, we present a large-scale audit of adult advertising on Twitter (now X), specifically...	true	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	false	393,852
2011.04452	Comparison between ARIMA and Deep Learning Models for Temperature Forecasting	Weather forecasting benefits us in various ways from farmers in cultivation and harvesting their crops to airlines to schedule their flights. Weather forecasting is a challenging task due to the chaotic nature of the atmosphere. Therefore lot of research attention has drawn to obtain the benefits and to overcome the ch...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	205,591
1901.01030	Multi-Product Dynamic Pricing in High-Dimensions with Heterogeneous Price Sensitivity	We consider the problem of multi-product dynamic pricing, in a contextual setting, for a seller of differentiated products. In this environment, the customers arrive over time and products are described by high-dimensional feature vectors. Each customer chooses a product according to the widely used Multinomial Logit (...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	117,907
1910.00571	Environmental drivers of systematicity and generalization in a situated agent	The question of whether deep neural networks are good at generalising beyond their immediate training experience is of critical importance for learning-based approaches to AI. Here, we consider tests of out-of-sample generalisation that require an agent to respond to never-seen-before instructions by manipulating and p...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	147,702
2312.09789	Optimization meets Machine Learning: An Exact Algorithm for Semi-Supervised Support Vector Machines	Support vector machines (SVMs) are well-studied supervised learning models for binary classification. In many applications, large amounts of samples can be cheaply and easily obtained. What is often a costly and error-prone process is to manually label these instances. Semi-supervised support vector machines (S3VMs) ex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	415,882
2108.06734	Effective and Efficient Graph Learning for Multi-view Clustering	Despite the impressive clustering performance and efficiency in characterizing both the relationship between data and cluster structure, existing graph-based multi-view clustering methods still have the following drawbacks. They suffer from the expensive time burden due to both the construction of graphs and eigen-deco...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	250,703
2205.02475	Speaker Recognition in the Wild	In this paper, we propose a pipeline to find the number of speakers, as well as audios belonging to each of these now identified speakers in a source of audio data where number of speakers or speaker labels are not known a priori. We used this approach as a part of our Data Preparation pipeline for Speech Recognition i...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	294,957
2308.14608	AI in the Gray: Exploring Moderation Policies in Dialogic Large Language Models vs. Human Answers in Controversial Topics	The introduction of ChatGPT and the subsequent improvement of Large Language Models (LLMs) have prompted more and more individuals to turn to the use of ChatBots, both for information and assistance with decision-making. However, the information the user is after is often not formulated by these ChatBots objectively en...	false	false	false	true	false	false	true	false	true	false	false	false	false	true	false	false	false	false	388,388
2101.00121	WARP: Word-level Adversarial ReProgramming	Transfer learning from pretrained language models recently became the dominant approach for solving many NLP tasks. A common approach to transfer learning for multiple tasks that maximize parameter sharing trains one or more task-specific layers on top of the language model. In this paper, we present an alternative app...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	213,968
2002.03733	Robust Multimodal Image Registration Using Deep Recurrent Reinforcement Learning	The crucial components of a conventional image registration method are the choice of the right feature representations and similarity measures. These two components, although elaborately designed, are somewhat handcrafted using human knowledge. To this end, these two components are tackled in an end-to-end manner via r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	163,377
1909.04905	SwarmMesh: A Distributed Data Structure for Cooperative Multi-Robot Applications	We present an approach to the distributed storage of data across a swarm of mobile robots that forms a shared global memory. We assume that external storage infrastructure is absent, and that each robot is capable of devoting a quota of memory and bandwidth to distributed storage. Our approach is motivated by the insig...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	144,938
2307.12730	COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts	Practical object detection application can lose its effectiveness on image inputs with natural distribution shifts. This problem leads the research community to pay more attention on the robustness of detectors under Out-Of-Distribution (OOD) inputs. Existing works construct datasets to benchmark the detector's OOD rob...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,361
2108.06721	Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time	In several real world applications, machine learning models are deployed to make predictions on data whose distribution changes gradually along time, leading to a drift between the train and test distributions. Such models are often re-trained on new data periodically, and they hence need to generalize to data not too ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	250,699
2011.06913	Finding optimal Pulse Repetion Intervals with Many-objective Evolutionary Algorithms	In this paper we consider the problem of finding Pulse Repetition Intervals allowing the best compromises mitigating range and Doppler ambiguities in a Pulsed-Doppler radar system. We revisit a problem that was proposed to the Evolutionary Computation community as a real-world case to test Many-objective Optimization a...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	206,384
2106.08799	Regularization-Induced Bias and Consistency in Recursive Least Squares	Within the context of recursive least squares (RLS) parameter estimation, the goal of the present paper is to study the effect of regularization-induced bias on the transient and asymptotic accuracy of the parameter estimates. We consider this question in three stages. First, we consider regression with random data, in...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	241,424
1302.3610	Testing Implication of Probabilistic Dependencies	Axiomatization has been widely used for testing logical implications. This paper suggests a non-axiomatic method, the chase, to test if a new dependency follows from a given set of probabilistic dependencies. Although the chase computation may require exponential time in some cases, this technique is a powerful tool fo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,076
2010.08246	SIGTYP 2020 Shared Task: Prediction of Typological Features	Typological knowledge bases (KBs) such as WALS (Dryer and Haspelmath, 2013) contain information about linguistic properties of the world's languages. They have been shown to be useful for downstream applications, including cross-lingual transfer learning and linguistic probing. A major drawback hampering broader adopti...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	201,123
2010.04661	Using Graph Neural Networks for Mass Spectrometry Prediction	Detecting and quantifying products of cellular metabolism using Mass Spectrometry (MS) has already shown great promise in many biological and biomedical applications. The biggest challenge in metabolomics is annotation, where measured spectra are assigned chemical identities. Despite advances, current methods provide l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	199,824
2405.09592	A Survey of Generative Techniques for Spatial-Temporal Data Mining	This paper focuses on the integration of generative techniques into spatial-temporal data mining, considering the significant growth and diverse nature of spatial-temporal data. With the advancements in RNNs, CNNs, and other non-generative techniques, researchers have explored their application in capturing temporal an...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	454,472
2406.03372	Training of Physical Neural Networks	Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research area with small-scale laboratory demonstrations, they are arguably one of the most underappreciated important opportunities in modern AI. Co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	461,212
2407.19512	Large-scale cervical precancerous screening via AI-assisted cytology whole slide image analysis	Cervical Cancer continues to be the leading gynecological malignancy, posing a persistent threat to women's health on a global scale. Early screening via cytology Whole Slide Image (WSI) diagnosis is critical to prevent this Cancer progression and improve survival rate, but pathologist's single test suffers inevitable ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	476,818
2208.08562	Restructurable Activation Networks	Is it possible to restructure the non-linear activation functions in a deep network to create hardware-efficient models? To address this question, we propose a new paradigm called Restructurable Activation Networks (RANs) that manipulate the amount of non-linearity in models to improve their hardware-awareness and effi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	313,392
2005.02057	Discrete-to-Deep Supervised Policy Learning	Neural networks are effective function approximators, but hard to train in the reinforcement learning (RL) context mainly because samples are correlated. For years, scholars have got around this by employing experience replay or an asynchronous parallel-agent system. This paper proposes Discrete-to-Deep Supervised Poli...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	175,746
2002.06862	Large-scale biometry with interpretable neural network regression on UK Biobank body MRI	In a large-scale medical examination, the UK Biobank study has successfully imaged more than 32,000 volunteer participants with magnetic resonance imaging (MRI). Each scan is linked to extensive metadata, providing a comprehensive medical survey of imaged anatomy and related health states. Despite its potential for res...	false	false	false	false	false	true	true	false	false	false	false	true	false	false	false	false	false	false	164,329
2205.04255	Improved Evaluation and Generation of Grid Layouts using Distance Preservation Quality and Linear Assignment Sorting	Images sorted by similarity enables more images to be viewed simultaneously, and can be very useful for stock photo agencies or e-commerce applications. Visually sorted grid layouts attempt to arrange images so that their proximity on the grid corresponds as closely as possible to their similarity. Various metrics exis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	295,583
2405.06687	Hire Me or Not? Examining Language Model's Behavior with Occupation Attributes	With the impressive performance in various downstream tasks, large language models (LLMs) have been widely integrated into production pipelines, like recruitment and recommendation systems. A known issue of models trained on natural language data is the presence of human biases, which can impact the fairness of the sys...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	453,400
2007.09141	Diversifying Anonymized Data with Diversity Constraints	Recently introduced privacy legislation has aimed to restrict and control the amount of personal data published by companies and shared to third parties. Much of this real data is not only sensitive requiring anonymization, but also contains characteristic details from a variety of individuals. This diversity is desira...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	187,840
2007.00806	Query-Free Adversarial Transfer via Undertrained Surrogates	Deep neural networks are vulnerable to adversarial examples -- minor perturbations added to a model's input which cause the model to output an incorrect prediction. We introduce a new method for improving the efficacy of adversarial attacks in a black-box setting by undertraining the surrogate model which the attacks a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	185,221
2409.01548	VoxHakka: A Dialectally Diverse Multi-speaker Text-to-Speech System for Taiwanese Hakka	This paper introduces VoxHakka, a text-to-speech (TTS) system designed for Taiwanese Hakka, a critically under-resourced language spoken in Taiwan. Leveraging the YourTTS framework, VoxHakka achieves high naturalness and accuracy and low real-time factor in speech synthesis while supporting six distinct Hakka dialects....	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	485,375
2501.08325	GameFactory: Creating New Games with Generative Interactive Videos	Generative game engines have the potential to revolutionize game development by autonomously creating new content and reducing manual workload. However, existing video-based game generation methods fail to address the critical challenge of scene generalization, limiting their applicability to existing games with fixed ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	524,720
2109.12586	Optimal Simulation of Quantum Measurements via the Likelihood POVMs	By developing a new framework of likelihood POVMs, analysis techniques and a new proof of the quantum covering lemma, we address the simulation of separable quantum measurement over bipartite states. In addition to a new one shot inner bound that naturally generalizes to the asymptotic case, we demonstrate the power, g...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	257,351
2110.00539	Applying Differential Privacy to Tensor Completion	Tensor completion aims at filling the missing or unobserved entries based on partially observed tensors. However, utilization of the observed tensors often raises serious privacy concerns in many practical scenarios. To address this issue, we propose a solid and unified framework that contains several approaches for ap...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	258,430
2411.07233	Score-based generative diffusion with "active" correlated noise sources	Diffusion models exhibit robust generative properties by approximating the underlying distribution of a dataset and synthesizing data by sampling from the approximated distribution. In this work, we explore how the generative performance may be be modulated if noise sources with temporal correlations -- akin to those u...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	507,450
2206.09418	LordNet: An Efficient Neural Network for Learning to Solve Parametric Partial Differential Equations without Simulated Data	Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential equations (PDE). However, it requires a large amount of simulated data, which can be costly to collect. This can be avo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	303,564
2407.06567	FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making	Large language models (LLMs) have demonstrated notable potential in conducting complex tasks and are increasingly utilized in various financial applications. However, high-quality sequential financial investment decision-making remains challenging. These tasks require multiple interactions with a volatile environment f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	471,449
0704.1455	A Better Good-Turing Estimator for Sequence Probabilities	We consider the problem of estimating the probability of an observed string drawn i.i.d. from an unknown distribution. The key feature of our study is that the length of the observed string is assumed to be of the same order as the size of the underlying alphabet. In this setting, many letters are unseen and the empiri...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	37
2402.00870	Prioritising Interactive Flows in Data Center Networks With Central Control	Data centers are on the rise and scientists are re-thinking and re-designing networks for data centers. The concept of central control which was not effective in the Internet era is now gaining popularity and is used in many data centers due to lower scale of operation (compared to Internet), structured topologies and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	425,760
2106.16037	Learning to Minimize Age of Information over an Unreliable Channel with Energy Harvesting	The time average expected age of information (AoI) is studied for status updates sent over an error-prone channel from an energy-harvesting transmitter with a finite-capacity battery. Energy cost of sensing new status updates is taken into account as well as the transmission energy cost better capturing practical syste...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	243,950
2304.13787	Surrogate Assisted Generation of Human-Robot Interaction Scenarios	As human-robot interaction (HRI) systems advance, so does the difficulty of evaluating and understanding the strengths and limitations of these systems in different environments and with different users. To this end, previous methods have algorithmically generated diverse scenarios that reveal system failures in a shar...	true	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	360,704
2209.06758	Timor Python: A Toolbox for Industrial Modular Robotics	Modular Reconfigurable Robots (MRRs) represent an exciting path forward for industrial robotics, opening up new possibilities for robot design. Compared to monolithic manipulators, they promise greater flexibility, improved maintainability, and cost-efficiency. However, there is no tool or standardized way to model and...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	317,499
1411.1680	State of Charge Evolution Equations for Flywheels	A mathematical state-of-charge evolution equation is present for Flywheel Energy Storage Systems.	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	37,361
0708.2273	Opportunism in Multiuser Relay Channels: Scheduling, Routing and Spectrum Reuse	In order to understand the key merits of multiuser diversity techniques in relay-assisted cellular multihop networks, this paper analyzes the spectral efficiency of opportunistic (i.e., channel-aware) scheduling algorithms over a fading multiuser relay channel with $K$ users in the asymptotic regime of large (but finit...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	559
2012.02258	WedgeChain: A Trusted Edge-Cloud Store With Asynchronous (Lazy) Trust	We propose WedgeChain, a data store that spans both edge and cloud nodes (an edge-cloud system). WedgeChain consists of a logging layer and a data indexing layer. In this study, we encounter two challenges: (1) edge nodes are untrusted and potentially malicious, and (2) edge-cloud coordination is expensive. WedgeChain ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	209,699
1610.08168	Location Aggregation of Spatial Population CTMC Models	In this paper we focus on spatial Markov population models, describing the stochastic evolution of populations of agents, explicitly modelling their spatial distribution, representing space as a discrete, finite graph. More specifically, we present a heuristic approach to aggregating spatial locations, which is designe...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	62,894
2303.11552	Boosting Verified Training for Robust Image Classifications via Abstraction	This paper proposes a novel, abstraction-based, certified training method for robust image classifiers. Via abstraction, all perturbed images are mapped into intervals before feeding into neural networks for training. By training on intervals, all the perturbed images that are mapped to the same interval are classified...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,895
1306.6125	Design and Implementation of an Unmanned Vehicle using a GSM Network with Microcontrollers	Now-a-days, a lot of research is being carried out in the development of USVs (Unmanned surface vehicles), UAVs (Unmanned Aerial Vehicles) etc. Now in case of USVs generally, we have seen that wireless controlled vehicles use RF circuits which suffer from many drawbacks such as limited working range, limited frequency ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	25,457
2304.06696	Improving novelty detection with generative adversarial networks on hand gesture data	We propose a novel way of solving the issue of classification of out-of-vocabulary gestures using Artificial Neural Networks (ANNs) trained in the Generative Adversarial Network (GAN) framework. A generative model augments the data set in an online fashion with new samples and stochastic target vectors, while a discrim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	358,062
2201.04924	Technical Report for ICCV 2021 Challenge SSLAD-Track3B: Transformers Are Better Continual Learners	In the SSLAD-Track 3B challenge on continual learning, we propose the method of COntinual Learning with Transformer (COLT). We find that transformers suffer less from catastrophic forgetting compared to convolutional neural network. The major principle of our method is to equip the transformer based feature extractor w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	275,236
2409.00800	Comparing Discrete and Continuous Space LLMs for Speech Recognition	This paper investigates discrete and continuous speech representations in Large Language Model (LLM)-based Automatic Speech Recognition (ASR), organizing them by feature continuity and training approach into four categories: supervised and unsupervised for both discrete and continuous types. We further classify LLMs ba...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	485,077
2403.06381	Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models	Recent advancements in diffusion models have notably improved the perceptual quality of generated images in text-to-image synthesis tasks. However, diffusion models often struggle to produce images that accurately reflect the intended semantics of the associated text prompts. We examine cross-attention layers in diffus...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,421
1906.08177	AI-enabled Blockchain: An Outlier-aware Consensus Protocol for Blockchain-based IoT Networks	A new framework for a secure and robust consensus in blockchain-based IoT networks is proposed using machine learning. Hyperledger fabric, which is a blockchain platform developed as part of the Hyperledger project, though looks very apt for IoT applications, has comparatively low tolerance for malicious activities in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	135,797
2405.11197	Designing NLP Systems That Adapt to Diverse Worldviews	Natural Language Inference (NLI) is foundational for evaluating language understanding in AI. However, progress has plateaued, with models failing on ambiguous examples and exhibiting poor generalization. We argue that this stems from disregarding the subjective nature of meaning, which is intrinsically tied to an indi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	455,040
2312.00596	BCN: Batch Channel Normalization for Image Classification	Normalization techniques have been widely used in the field of deep learning due to their capability of enabling higher learning rates and are less careful in initialization. However, the effectiveness of popular normalization technologies is typically limited to specific areas. Unlike the standard Batch Normalization ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	412,106
1808.07412	Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks	Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady state (the throughput) is important for both compiler designers and performance engineers. Building an analytical model to do so is especially complicated in modern x86-64 Complex Instruction Set Computer (CISC...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	105,736
2407.07457	GLBench: A Comprehensive Benchmark for Graph with Large Language Models	The emergence of large language models (LLMs) has revolutionized the way we interact with graphs, leading to a new paradigm called GraphLLM. Despite the rapid development of GraphLLM methods in recent years, the progress and understanding of this field remain unclear due to the lack of a benchmark with consistent exper...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	471,769
2309.14998	An Ensemble Model for Distorted Images in Real Scenarios	Image acquisition conditions and environments can significantly affect high-level tasks in computer vision, and the performance of most computer vision algorithms will be limited when trained on distortion-free datasets. Even with updates in hardware such as sensors and deep learning methods, it will still not work in ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,813
2405.13020	Using Combinatorial Optimization to Design a High quality LLM Solution	We introduce a novel LLM based solution design approach that utilizes combinatorial optimization and sampling. Specifically, a set of factors that influence the quality of the solution are identified. They typically include factors that represent prompt types, LLM inputs alternatives, and parameters governing the gener...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	455,753
1301.1671	Causal graph-based video segmentation	Numerous approaches in image processing and computer vision are making use of super-pixels as a pre-processing step. Among the different methods producing such over-segmentation of an image, the graph-based approach of Felzenszwalb and Huttenlocher is broadly employed. One of its interesting properties is that the regi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	20,874
1909.05645	Learning Alignment for Multimodal Emotion Recognition from Speech	Speech emotion recognition is a challenging problem because human convey emotions in subtle and complex ways. For emotion recognition on human speech, one can either extract emotion related features from audio signals or employ speech recognition techniques to generate text from speech and then apply natural language p...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	145,152
1911.12425	Learning with less data via Weakly Labeled Patch Classification in Digital Pathology	In Digital Pathology (DP), labeled data is generally very scarce due to the requirement that medical experts provide annotations. We address this issue by learning transferable features from weakly labeled data, which are collected from various parts of the body and are organized by non-medical experts. In this paper, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	155,384
2110.08443	Prix-LM: Pretraining for Multilingual Knowledge Base Construction	Knowledge bases (KBs) contain plenty of structured world and commonsense knowledge. As such, they often complement distributional text-based information and facilitate various downstream tasks. Since their manual construction is resource- and time-intensive, recent efforts have tried leveraging large pretrained languag...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	261,401
2308.06383	U-RED: Unsupervised 3D Shape Retrieval and Deformation for Partial Point Clouds	In this paper, we propose U-RED, an Unsupervised shape REtrieval and Deformation pipeline that takes an arbitrary object observation as input, typically captured by RGB images or scans, and jointly retrieves and deforms the geometrically similar CAD models from a pre-established database to tightly match the target. Co...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,114
2310.19936	Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient ?	For specialized and dense downstream tasks such as object detection, labeling data requires expertise and can be very expensive, making few-shot and semi-supervised models much more attractive alternatives. While in the few-shot setup we observe that transformer-based object detectors perform better than convolution-ba...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	404,189
1709.06222	Fast Discrete Linear Canonical Transform Based on CM-CC-CM Decomposition and FFT	In this paper, a discrete LCT (DLCT) irrelevant to the sampling periods and without oversampling operation is developed. This DLCT is based on the well-known CM-CC-CM decomposition, that is, implemented by two discrete chirp multiplications (CMs) and one discrete chirp convolution (CC). This decomposition doesn't use a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	81,060
2307.04816	Q-YOLO: Efficient Inference for Real-time Object Detection	Real-time object detection plays a vital role in various computer vision applications. However, deploying real-time object detectors on resource-constrained platforms poses challenges due to high computational and memory requirements. This paper describes a low-bit quantization method to build a highly efficient one-st...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	378,522
2401.07783	Cybersecurity and Embodiment Integrity for Modern Robots: A Conceptual Framework	Modern robots are stepping away from monolithic entities built using ad-hoc sensors and actuators, due to new technologies and communication paradigms, such as the Internet of Things (IoT) and the Robotic Operating System (ROS). Using such paradigms, robots can be built by acquiring heterogeneous standard devices and p...	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	421,655
1907.06337	Energy-efficient Path Planning for Ground Robots by Combining Air and Ground Measurements	As mobile robots find increasing use in outdoor applications, designing energy-efficient robot navigation algorithms is gaining importance. There are two primary approaches to energy efficient navigation: Offline approaches rely on a previously built energy map as input to a path planner. Obtaining energy maps for larg...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	138,595
2201.11483	Edge effects in radial porosity profiles from CT measurements and melt pool signal intensities for laser powder bed fusion	Limited process control can cause metallurgical defect formation and inhomogeneous relative density in laser powder bed fusion manufactured parts. In this study, cylindrical 15-5 PH stainless steel specimens are investigated by computer tomography; it shows an edge enhanced relative density profile. Additionally, the o...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	277,311
1601.03210	The scarcity of crossing dependencies: a direct outcome of a specific constraint?	The structure of a sentence can be represented as a network where vertices are words and edges indicate syntactic dependencies. Interestingly, crossing syntactic dependencies have been observed to be infrequent in human languages. This leads to the question of whether the scarcity of crossings in languages arises from ...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	50,893
2309.14893	A Passive Variable Impedance Control Strategy with Viscoelastic Parameters Estimation of Soft Tissues for Safe Ultrasonography	In the context of telehealth, robotic approaches have proven a valuable solution to in-person visits in remote areas, with decreased costs for patients and infection risks. In particular, in ultrasonography, robots have the potential to reproduce the skills required to acquire high-quality images while reducing the son...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	394,775
2311.05265	Don't Waste a Single Annotation: Improving Single-Label Classifiers Through Soft Labels	In this paper, we address the limitations of the common data annotation and training methods for objective single-label classification tasks. Typically, when annotating such tasks annotators are only asked to provide a single label for each sample and annotator disagreement is discarded when a final hard label is decid...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	406,529
1708.05038	ConvNet Architecture Search for Spatiotemporal Feature Learning	Learning image representations with ConvNets by pre-training on ImageNet has proven useful across many visual understanding tasks including object detection, semantic segmentation, and image captioning. Although any image representation can be applied to video frames, a dedicated spatiotemporal representation is still ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	79,064
1912.01448	Hierarchical model-based policy optimization: from actions to action sequences and back	We develop a normative framework for hierarchical model-based policy optimization based on applying second-order methods in the space of all possible state-action paths. The resulting natural path gradient performs policy updates in a manner which is sensitive to the long-range correlational structure of the induced st...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	156,089
1812.11226	Fast Training Algorithms for Deep Convolutional Fuzzy Systems with Application to Stock Index Prediction	A deep convolutional fuzzy system (DCFS) on a high-dimensional input space is a multi-layer connection of many low-dimensional fuzzy systems, where the input variables to the low-dimensional fuzzy systems are selected through a moving window across the input spaces of the layers. To design the DCFS based on input-outpu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	117,517
2302.10891	An Implicit GNN Solver for Poisson-like problems	This paper presents $\Psi$-GNN, a novel Graph Neural Network (GNN) approach for solving the ubiquitous Poisson PDE problems with mixed boundary conditions. By leveraging the Implicit Layer Theory, $\Psi$-GNN models an "infinitely" deep network, thus avoiding the empirical tuning of the number of required Message Passin...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	346,997
1010.3467	Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition	Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of these bases. The applicability of these methods to visual object recognition tasks has been limited because of the prohibitive cost of the opt...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	7,928
2010.01618	A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network	Incorporating a so-called "momentum" dynamic in gradient descent methods is widely used in neural net training as it has been broadly observed that, at least empirically, it often leads to significantly faster convergence. At the same time, there are very few theoretical guarantees in the literature to explain this app...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	198,715
1711.07465	Better Agnostic Clustering Via Relaxed Tensor Norms	We develop a new family of convex relaxations for $k$-means clustering based on sum-of-squares norms, a relaxation of the injective tensor norm that is efficiently computable using the Sum-of-Squares algorithm. We give an algorithm based on this relaxation that recovers a faithful approximation to the true means in the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,001
1509.04524	Open Access and Discovery Tools: How do Primo Libraries Manage Green Open Access Collections?	Scholarly Open Access repositories contain lots of treasures including rare or otherwise unpublished materials and articles that scholars self-archive, often as part of their institution's mandate. But it can be hard to discover this material unless users know exactly where to look. Since the very beginning, libraries ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	46,940
1908.04568	Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection	Midline shift (MLS) is a well-established factor used for outcome prediction in traumatic brain injury, stroke and brain tumors. The importance of automatic estimation of MLS was recently highlighted by ACR Data Science Institute. In this paper we introduce a novel deep learning based approach for the problem of MLS de...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	141,519
2110.09089	DNA Codes over the Ring $\mathbb{Z}_4 + w\mathbb{Z}_4$	In this present work, we generalize the study of construction of DNA codes over the rings $\mathcal{R}_\theta=\mathbb{Z}_4+w\mathbb{Z}_4$, $w^2 = \theta $ for $\theta \in \mathbb{Z}_4+w\mathbb{Z}_4$. Rigorous study along with characterization of the ring structures is presented. We extend the Gau map and Gau distance, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	261,674
1707.09866	Guided Co-training for Large-Scale Multi-View Spectral Clustering	In many real-world applications, we have access to multiple views of the data, each of which characterizes the data from a distinct aspect. Several previous algorithms have demonstrated that one can achieve better clustering accuracy by integrating information from all views appropriately than using only an individual ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,097
1205.4551	Sparse Signal Separation in Redundant Dictionaries	We formulate a unified framework for the separation of signals that are sparse in "morphologically" different redundant dictionaries. This formulation incorporates the so-called "analysis" and "synthesis" approaches as special cases and contains novel hybrid setups. We find corresponding coherence-based recovery guaran...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,105
2207.08064	Detecting Humans in RGB-D Data with CNNs	We address the problem of people detection in RGB-D data where we leverage depth information to develop a region-of-interest (ROI) selection method that provides proposals to two color and depth CNNs. To combine the detections produced by the two CNNs, we propose a novel fusion approach based on the characteristics of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	308,444
2105.13783	Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems	Regression problems have been widely studied in machinelearning literature resulting in a plethora of regression models and performance measures. However, there are few techniques specially dedicated to solve the problem of how to incorporate categorical features to regression problems. Usually, categorical feature enc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	237,403
2202.11629	A Complete Criterion for Value of Information in Soluble Influence Diagrams	Influence diagrams have recently been used to analyse the safety and fairness properties of AI systems. A key building block for this analysis is a graphical criterion for value of information (VoI). This paper establishes the first complete graphical criterion for VoI in influence diagrams with multiple decisions. Alo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	281,941

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