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
2309.15204	CLRmatchNet: Enhancing Curved Lane Detection with Deep Matching Process	Lane detection plays a crucial role in autonomous driving by providing vital data to ensure safe navigation. Modern algorithms rely on anchor-based detectors, which are then followed by a label-assignment process to categorize training detections as positive or negative instances based on learned geometric attributes. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,879
1806.04935	Convolutional sparse coding for capturing high speed video content	Video capture is limited by the trade-off between spatial and temporal resolution: when capturing videos of high temporal resolution, the spatial resolution decreases due to bandwidth limitations in the capture system. Achieving both high spatial and temporal resolution is only possible with highly specialized and very...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	100,353
2408.13373	Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set Recognition	Few-shot open-set recognition (FSOR) is a challenging task that requires a model to recognize known classes and identify unknown classes with limited labeled data. Existing approaches, particularly Negative-Prototype-Based methods, generate negative prototypes based solely on known class data. However, as the unknown s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	483,121
2206.06807	The Causal Structure of Semantic Ambiguities	Ambiguity is a natural language phenomenon occurring at different levels of syntax, semantics, and pragmatics. It is widely studied; in Psycholinguistics, for instance, we have a variety of competing studies for the human disambiguation processes. These studies are empirical and based on eye-tracking measurements. Here...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	302,508
2310.13011	Compositional preference models for aligning LMs	As language models (LMs) become more capable, it is increasingly important to align them with human preferences. However, the dominant paradigm for training Preference Models (PMs) for that purpose suffers from fundamental limitations, such as lack of transparency and scalability, along with susceptibility to overfitti...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	401,252
2306.09215	On the Effects and Optimal Design of Redundant Sensors in Collaborative State Estimation	The existence of redundant sensors in collaborative state estimation is a common occurrence, yet their true significance remains elusive. This paper comprehensively investigates the effects and optimal design of redundant sensors in sensor networks that use Kalman filtering to estimate the state of a random process col...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	373,722
2311.00300	Entity Alignment Method of Science and Technology Patent based on Graph Convolution Network and Information Fusion	The entity alignment of science and technology patents aims to link the equivalent entities in the knowledge graph of different science and technology patent data sources. Most entity alignment methods only use graph neural network to obtain the embedding of graph structure or use attribute text description to obtain s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	404,593
2501.15893	Benchmarking Quantum Reinforcement Learning	Benchmarking and establishing proper statistical validation metrics for reinforcement learning (RL) remain ongoing challenges, where no consensus has been established yet. The emergence of quantum computing and its potential applications in quantum reinforcement learning (QRL) further complicate benchmarking efforts. T...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	527,751
2212.04354	Device identification using optimized digital footprints	The rapidly increasing number of internet of things (IoT) and non-IoT devices has imposed new security challenges to network administrators. Accurate device identification in the increasingly complex network structures is necessary. In this paper, a device fingerprinting (DFP) method has been proposed for device identi...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	335,415
1609.05815	Generalized Fano and non-Fano networks	It is known that the Fano network has a vector linear solution if and only if the characteristic of the finite field is $2$; and the non-Fano network has a vector linear solution if and only if the characteristic of the finite field is not $2$. Using these properties of Fano and non-Fano networks it has been shown that...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	61,201
2203.09936	Fake News Detection Using Majority Voting Technique	Due to the evolution of the Web and social network platforms it becomes very easy to disseminate the information. Peoples are creating and sharing more information than ever before, which may be misleading, misinformation or fake information. Fake news detection is a crucial and challenging task due to the unstructured...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	286,342
cs/0511065	Performance Analysis of MIMO-MRC in Double-Correlated Rayleigh Environments	We consider multiple-input multiple-output (MIMO) transmit beamforming systems with maximum ratio combining (MRC) receivers. The operating environment is Rayleigh-fading with both transmit and receive spatial correlation. We present exact expressions for the probability density function (p.d.f.) of the output signal-to...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,087
1804.02047	Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond	State-of-the-art pedestrian detection models have achieved great success in many benchmarks. However, these models require lots of annotation information and the labeling process usually takes much time and efforts. In this paper, we propose a method to generate labeled pedestrian data and adapt them to support the tra...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	94,328
2211.10748	Delay-aware Backpressure Routing Using Graph Neural Networks	We propose a throughput-optimal biased backpressure (BP) algorithm for routing, where the bias is learned through a graph neural network that seeks to minimize end-to-end delay. Classical BP routing provides a simple yet powerful distributed solution for resource allocation in wireless multi-hop networks but has poor d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,422
2405.08038	Feature Expansion and enhanced Compression for Class Incremental Learning	Class incremental learning consists in training discriminative models to classify an increasing number of classes over time. However, doing so using only the newly added class data leads to the known problem of catastrophic forgetting of the previous classes. Recently, dynamic deep learning architectures have been show...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	453,968
2310.08210	CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive Learning	Since satellite systems are playing an increasingly important role in our civilization, their security and privacy weaknesses are more and more concerned. For example, prior work demonstrates that the communication channel between maritime VSAT and ground segment can be eavesdropped on using consumer-grade equipment. T...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	399,308
2004.05125	Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned	We present the Neural Covidex, a search engine that exploits the latest neural ranking architectures to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institute for AI. This web application exists as part of a suite of tools that we have developed over the past few weeks to help d...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	true	172,097
2203.02635	Training privacy-preserving video analytics pipelines by suppressing features that reveal information about private attributes	Deep neural networks are increasingly deployed for scene analytics, including to evaluate the attention and reaction of people exposed to out-of-home advertisements. However, the features extracted by a deep neural network that was trained to predict a specific, consensual attribute (e.g. emotion) may also encode and t...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	283,805
2012.06981	Fine-Grained Lineage for Safer Notebook Interactions	Computational notebooks have emerged as the platform of choice for data science and analytical workflows, enabling rapid iteration and exploration. By keeping intermediate program state in memory and segmenting units of execution into so-called "cells", notebooks allow users to execute their workflows interactively and...	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	211,299
2103.11282	Tracking error learning control for precise mobile robot path tracking in outdoor environment	This paper presents a Tracking-Error Learning Control (TELC) algorithm for precise mobile robot path tracking in off-road terrain. In traditional tracking error-based control approaches, feedback and feedforward controllers are designed based on the nominal model which cannot capture the uncertainties, disturbances and...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	225,743
2210.01745	Making Decisions under Outcome Performativity	Decision-makers often act in response to data-driven predictions, with the goal of achieving favorable outcomes. In such settings, predictions don't passively forecast the future; instead, predictions actively shape the distribution of outcomes they are meant to predict. This performative prediction setting raises new ...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	321,375
2410.10322	Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks	In this work, we investigate a particular implicit bias in the gradient descent training process, which we term "Feature Averaging", and argue that it is one of the principal factors contributing to non-robustness of deep neural networks. Despite the existence of multiple discriminative features capable of classifying ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,017
2007.08553	Smooth Deformation Field-based Mismatch Removal in Real-time	This paper studies the mismatch removal problem, which may serve as the subsequent step of feature matching. Non-rigid deformation makes it difficult to remove mismatches because no parametric transformation can be found. To solve this problem, we first propose an algorithm based on the re-weighting and 1-point RANSAC ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	187,660
1505.04560	On the Formation of Circles in Co-authorship Networks	The availability of an overwhelmingly large amount of bibliographic information including citation and co-authorship data makes it imperative to have a systematic approach that will enable an author to organize her own personal academic network profitably. An effective method could be to have one's co-authorship networ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	43,202
2105.05566	Structural risk minimization for quantum linear classifiers	Quantum machine learning (QML) models based on parameterized quantum circuits are often highlighted as candidates for quantum computing's near-term ``killer application''. However, the understanding of the empirical and generalization performance of these models is still in its infancy. In this paper we study how to ba...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	234,855
1608.00698	Covert Communication in the Presence of an Uninformed Jammer	Recent work has established that when transmitter Alice wishes to communicate reliably to recipient Bob without detection by warden Willie, with additive white Gaussian noise (AWGN) channels between all parties, communication is limited to $\mathcal{O}(\sqrt{n})$ bits in $n$ channel uses. However, this assumes Willie h...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	59,321
2008.05932	Kullback-Leibler divergence between quantum distributions, and its upper-bound	This work presents an upper-bound to value that the Kullback-Leibler (KL) divergence can reach for a class of probability distributions called quantum distributions (QD). The aim is to find a distribution $U$ which maximizes the KL divergence from a given distribution $P$ under the assumption that $P$ and $U$ have been...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	191,659
2107.04618	Optimal Triangulation Method is Not Really Optimal	Triangulation refers to the problem of finding a 3D point from its 2D projections on multiple camera images. For solving this problem, it is the common practice to use so-called optimal triangulation method, which we call the L2 method in this paper. But, the method can be optimal only if we assume no uncertainty in th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	245,512
2207.03807	Beyond Transfer Learning: Co-finetuning for Action Localisation	Transfer learning is the predominant paradigm for training deep networks on small target datasets. Models are typically pretrained on large ``upstream'' datasets for classification, as such labels are easy to collect, and then finetuned on ``downstream'' tasks such as action localisation, which are smaller due to their...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	306,984
1805.08365	Learning Markov Clustering Networks for Scene Text Detection	A novel framework named Markov Clustering Network (MCN) is proposed for fast and robust scene text detection. MCN predicts instance-level bounding boxes by firstly converting an image into a Stochastic Flow Graph (SFG) and then performing Markov Clustering on this graph. Our method can detect text objects with arbitrar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	98,120
2309.17313	Few-Shot Domain Adaptation for Charge Prediction on Unprofessional Descriptions	Recent works considering professional legal-linguistic style (PLLS) texts have shown promising results on the charge prediction task. However, unprofessional users also show an increasing demand on such a prediction service. There is a clear domain discrepancy between PLLS texts and non-PLLS texts expressed by those la...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	395,722
2407.18421	Self-Directed Synthetic Dialogues and Revisions Technical Report	Synthetic data has become an important tool in the fine-tuning of language models to follow instructions and solve complex problems. Nevertheless, the majority of open data to date is often lacking multi-turn data and collected on closed models, limiting progress on advancing open fine-tuning methods. We introduce Self...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	476,356
2405.06705	LLMs can Find Mathematical Reasoning Mistakes by Pedagogical Chain-of-Thought	Self-correction is emerging as a promising approach to mitigate the issue of hallucination in Large Language Models (LLMs). To facilitate effective self-correction, recent research has proposed mistake detection as its initial step. However, current literature suggests that LLMs often struggle with reliably identifying...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	453,416
2203.10107	SiMCa: Sinkhorn Matrix Factorization with Capacity Constraints	For a very broad range of problems, recommendation algorithms have been increasingly used over the past decade. In most of these algorithms, the predictions are built upon user-item affinity scores which are obtained from high-dimensional embeddings of items and users. In more complex scenarios, with geometrical or cap...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	286,400
2309.08737	Experimental Assessment of a Forward-Collision Warning System Fusing Deep Learning and Decentralized Radio Sensing	This paper presents the idea of an automatic forward-collision warning system based on a decentralized radio sensing (RS) approach. In this framework, a vehicle in receiving mode employs a continuous waveform (CW) transmitted by a second vehicle as a probe signal to detect oncoming vehicles and warn the driver of a pot...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	392,297
1904.10597	Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning	Modern power grids are experiencing grand challenges caused by the stochastic and dynamic nature of growing renewable energy and demand response. Traditional theoretical assumptions and operational rules may be violated, which are difficult to be adapted by existing control systems due to the lack of computational powe...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	128,658
2201.03028	Development of a hybrid machine-learning and optimization tool for performance-based solar shading design	Solar shading design should be done for the desired Indoor Environmental Quality (IEQ) in the early design stages. This field can be very challenging and time-consuming also requires experts, sophisticated software, and a large amount of money. The primary purpose of this research is to design a simple tool to study va...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	274,732
2211.15782	Towards Preserving Semantic Structure in Argumentative Multi-Agent via Abstract Interpretation	Over the recent twenty years, argumentation has received considerable attention in the fields of knowledge representation, reasoning, and multi-agent systems. However, argumentation in dynamic multi-agent systems encounters the problem of significant arguments generated by agents, which comes at the expense of represen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	333,390
2308.09952	Finding emergence in data by maximizing effective information	Quantifying emergence and modeling emergent dynamics in a data-driven manner for complex dynamical systems is challenging due to the lack of direct observations at the micro-level. Thus, it's crucial to develop a framework to identify emergent phenomena and capture emergent dynamics at the macro-level using available d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	386,503
1606.00094	Boda-RTC: Productive Generation of Portable, Efficient Code for Convolutional Neural Networks on Mobile Computing Platforms	The popularity of neural networks (NNs) spans academia, industry, and popular culture. In particular, convolutional neural networks (CNNs) have been applied to many image based machine learning tasks and have yielded strong results. The availability of hardware/software systems for efficient training and deployment of ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	56,625
2311.00136	Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data	State-of-the-art systems neuroscience experiments yield large-scale multimodal data, and these data sets require new tools for analysis. Inspired by the success of large pretrained models in vision and language domains, we reframe the analysis of large-scale, cellular-resolution neuronal spiking data into an autoregres...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	404,520
2002.09703	Automatic Data Augmentation via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation	Conventional data augmentation realized by performing simple pre-processing operations (\eg, rotation, crop, \etc) has been validated for its advantage in enhancing the performance for medical image segmentation. However, the data generated by these conventional augmentation methods are random and sometimes harmful to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	165,154
1706.05723	Detecting Large Concept Extensions for Conceptual Analysis	When performing a conceptual analysis of a concept, philosophers are interested in all forms of expression of a concept in a text---be it direct or indirect, explicit or implicit. In this paper, we experiment with topic-based methods of automating the detection of concept expressions in order to facilitate philosophica...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	75,561
2408.11316	Probabilistic Medical Predictions of Large Language Models	Large Language Models (LLMs) have shown promise in clinical applications through prompt engineering, allowing flexible clinical predictions. However, they struggle to produce reliable prediction probabilities, which are crucial for transparency and decision-making. While explicit prompts can lead LLMs to generate proba...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	482,233
2409.14495	Thought-Path Contrastive Learning via Premise-Oriented Data Augmentation for Logical Reading Comprehension	Logical reading comprehension is a challenging task that entails grasping the underlying semantics of text and applying reasoning to deduce the correct answer. Prior researches have primarily focused on enhancing logical reasoning capabilities through Chain-of-Thought (CoT) or data augmentation. However, previous work ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	490,492
2501.10122	Integrating Mediumband with Emerging Technologies: Unified Vision for 6G and Beyond Physical Layer	In this paper, we present a vision for the physical layer of 6G and beyond, where emerging physical layer technologies integrate to drive wireless links toward mediumband operation, addressing a major challenge: deep fading, a prevalent, and perhaps the most consequential, obstacle in wireless communication link perfor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	525,400
2003.04614	Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation	Unsupervised domain adaptation enables to alleviate the need for pixel-wise annotation in the semantic segmentation. One of the most common strategies is to translate images from the source domain to the target domain and then align their marginal distributions in the feature space using adversarial learning. However, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,599
2004.06307	Sense and Sensibility: Characterizing Social Media Users Regarding the Use of Controversial Terms for COVID-19	With the world-wide development of 2019 novel coronavirus, although WHO has officially announced the disease as COVID-19, one controversial term - "Chinese Virus" is still being used by a great number of people. In the meantime, global online media coverage about COVID-19-related racial attacks increases steadily, most...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	172,472
2112.07839	LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization	Federated optimization (FedOpt), which targets at collaboratively training a learning model across a large number of distributed clients, is vital for federated learning. The primary concerns in FedOpt can be attributed to the model divergence and communication efficiency, which significantly affect the performance. In...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	271,602
1903.07107	Adaptive Genomic Evolution of Neural Network Topologies (AGENT) for State-to-Action Mapping in Autonomous Agents	Neuroevolution is a process of training neural networks (NN) through an evolutionary algorithm, usually to serve as a state-to-action mapping model in control or reinforcement learning-type problems. This paper builds on the Neuro Evolution of Augmented Topologies (NEAT) formalism that allows designing topology and wei...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	false	false	124,535
1901.02033	The Effect of Introducing Redundancy in a Probabilistic Forwarding Protocol	This paper is concerned with the problem of broadcasting information from a source node to every node in an ad-hoc network. Flooding, as a broadcast mechanism, involves each node forwarding any packet it receives to all its neighbours. This results in excessive transmissions and thus a high energy expenditure overall. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	118,105
2310.01846	Benchmarking and Improving Generator-Validator Consistency of Language Models	As of September 2023, ChatGPT correctly answers "what is 7+8" with 15, but when asked "7+8=15, True or False" it responds with "False". This inconsistency between generating and validating an answer is prevalent in language models (LMs) and erodes trust. In this paper, we propose a framework for measuring the consisten...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	396,605
2409.10986	Control-flow Reconstruction Attacks on Business Process Models	Process models may be automatically generated from event logs that contain as-is data of a business process. While such models generalize over the control-flow of specific, recorded process executions, they are often also annotated with behavioural statistics, such as execution frequencies.Based thereon, once a model i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	true	488,963
2305.06595	BanglaBook: A Large-scale Bangla Dataset for Sentiment Analysis from Book Reviews	The analysis of consumer sentiment, as expressed through reviews, can provide a wealth of insight regarding the quality of a product. While the study of sentiment analysis has been widely explored in many popular languages, relatively less attention has been given to the Bangla language, mostly due to a lack of relevan...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	363,604
1910.01909	On some distributed scheduling algorithms for wireless networks with hypergraph interference models	It is shown that the performance of the maximal scheduling algorithm in wireless ad hoc networks under the hypergraph interference model can be further away from optimal than previously known. The exact worst-case performance of this distributed, greedy scheduling algorithm is analyzed.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	148,079
2409.15934	Automated test generation to evaluate tool-augmented LLMs as conversational AI agents	Tool-augmented LLMs are a promising approach to create AI agents that can have realistic conversations, follow procedures, and call appropriate functions. However, evaluating them is challenging due to the diversity of possible conversations, and existing datasets focus only on single interactions and function-calling....	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	491,135
2311.13732	A Propagation Perspective on Recursive Forward Dynamics for Systems with Kinematic Loops	We revisit the concept of constraint embedding as a means for dealing with kinematic loop constraints during dynamics computations for rigid-body systems. Specifically, we consider the local loop constraints emerging from common actuation sub-mechanisms in modern robotics systems (e.g., geared motors, differential driv...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	409,852
2407.11087	Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKV	Transformers have revolutionized medical image restoration, but the quadratic complexity still poses limitations for their application to high-resolution medical images. The recent advent of the Receptance Weighted Key Value (RWKV) model in the natural language processing field has attracted much attention due to its a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,300
1901.09541	On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis	In this paper, we study random subsampling of Gaussian process regression, one of the simplest approximation baselines, from a theoretical perspective. Although subsampling discards a large part of training data, we show provable guarantees on the accuracy of the predictive mean/variance and its generalization ability....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	119,779
1611.04211	On Location Hiding in Distributed Systems	We consider the following problem - a group of mobile agents perform some task on a terrain modeled as a graph. In a given moment of time an adversary gets an access to the graph and positions of the agents. Shortly before adversary's observation the mobile agents have a chance to relocate themselves in order to hide t...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	63,805
1707.03997	A Web-Based Tool for Analysing Normative Documents in English	Our goal is to use formal methods to analyse normative documents written in English, such as privacy policies and service-level agreements. This requires the combination of a number of different elements, including information extraction from natural language, formal languages for model representation, and an interface...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	76,970
1711.01526	On Identification of Distribution Grids	Large-scale integration of distributed energy resources into residential distribution feeders necessitates careful control of their operation through power flow analysis. While the knowledge of the distribution system model is crucial for this type of analysis, it is often unavailable or outdated. The recent introducti...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	83,905
1610.08885	Optimal actuator placement for minimizing the worst-case control energy	We consider the actuator placement problem for linear systems. Specifically, we aim to identify an actuator which requires the least amount of control energy to drive the system from an arbitrary initial condition to the origin in the worst case. Said otherwise, we investigate the minimax problem of minimizing the cont...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	62,979
2206.00667	How Biased are Your Features?: Computing Fairness Influence Functions with Global Sensitivity Analysis	Fairness in machine learning has attained significant focus due to the widespread application in high-stake decision-making tasks. Unregulated machine learning classifiers can exhibit bias towards certain demographic groups in data, thus the quantification and mitigation of classifier bias is a central concern in fairn...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	300,206
1112.2491	Permutation Excess Entropy and Mutual Information between the Past and Future	We address the excess entropy, which is a measure of complexity for stationary time series, from the ordinal point of view. We show that the permutation excess entropy is equal to the mutual information between two adjacent semi-infinite blocks in the space of orderings for finite-state stationary ergodic Markov proces...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	13,423
2103.11623	Multi-Transmitter Coded Caching Networks with Transmitter-side Knowledge of File Popularity	This work presents a new way of exploiting non-uniform file popularity in coded caching networks. Focusing on a fully-connected fully-interfering wireless setting with multiple cache-enabled transmitters and receivers, we show how non-uniform file popularity can be used very efficiently to accelerate the impact of tran...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	225,877
1703.10661	BanglaLekha-Isolated: A Comprehensive Bangla Handwritten Character Dataset	Bangla handwriting recognition is becoming a very important issue nowadays. It is potentially a very important task specially for Bangla speaking population of Bangladesh and West Bengal. By keeping that in our mind we are introducing a comprehensive Bangla handwritten character dataset named BanglaLekha-Isolated. This...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	70,949
2205.06468	Monocular Human Digitization via Implicit Re-projection Networks	We present an approach to generating 3D human models from images. The key to our framework is that we predict double-sided orthographic depth maps and color images from a single perspective projected image. Our framework consists of three networks. The first network predicts normal maps to recover geometric details suc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	296,247
1910.08945	Online Bagging for Anytime Transfer Learning	Transfer learning techniques have been widely used in the reality that it is difficult to obtain sufficient labeled data in the target domain, but a large amount of auxiliary data can be obtained in the relevant source domain. But most of the existing methods are based on offline data. In practical applications, it is ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	150,025
2207.05983	Data-Driven Identification of Dynamic Quality Models in Drinking Water Networks	Traditional control and monitoring of water quality in drinking water distribution networks (WDN) rely on mostly model- or toolbox-driven approaches, where the network topology and parameters are assumed to be known. In contrast, system identification (SysID) algorithms for generic dynamic system models seek to approxi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	307,732
2007.13055	Optimizing Block-Sparse Matrix Multiplications on CUDA with TVM	We implemented and optimized matrix multiplications between dense and block-sparse matrices on CUDA. We leveraged TVM, a deep learning compiler, to explore the schedule space of the operation and generate efficient CUDA code. With the automatic parameter tuning in TVM, our cross-thread reduction based implementation ac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	189,007
2102.02485	Image Restoration by Deep Projected GSURE	Ill-posed inverse problems appear in many image processing applications, such as deblurring and super-resolution. In recent years, solutions that are based on deep Convolutional Neural Networks (CNNs) have shown great promise. Yet, most of these techniques, which train CNNs using external data, are restricted to the ob...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	218,422
1812.11718	Over- and Under-Approximating Reachable Sets for Perturbed Delay Differential Equations	This note explores reach set computations for perturbed delay differential equations (DDEs). The perturbed DDEs of interest in this note is a class of DDEs whose dynamics are subject to perturbations, and their solutions feature the local homeomorphism property with respect to initial states. Membership in this class o...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	117,616
1106.0895	Computable Bounds for Rate Distortion with Feed-Forward for Stationary and Ergodic Sources	In this paper we consider the rate distortion problem of discrete-time, ergodic, and stationary sources with feed forward at the receiver. We derive a sequence of achievable and computable rates that converge to the feed-forward rate distortion. We show that, for ergodic and stationary sources, the rate {align} R_n(D)=...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,728
2411.18268	Information geometry of bosonic Gaussian thermal states	Bosonic Gaussian thermal states form a fundamental class of states in quantum information science. This paper explores the information geometry of these states, focusing on characterizing the distance between two nearby states and the geometry induced by a parameterization in terms of their mean vectors and Hamiltonian...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	511,801
2409.00815	Serialized Speech Information Guidance with Overlapped Encoding Separation for Multi-Speaker Automatic Speech Recognition	Serialized output training (SOT) attracts increasing attention due to its convenience and flexibility for multi-speaker automatic speech recognition (ASR). However, it is not easy to train with attention loss only. In this paper, we propose the overlapped encoding separation (EncSep) to fully utilize the benefits of th...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	485,081
2302.01999	Online and Offline Learning of Player Objectives from Partial Observations in Dynamic Games	Robots deployed to the real world must be able to interact with other agents in their environment. Dynamic game theory provides a powerful mathematical framework for modeling scenarios in which agents have individual objectives and interactions evolve over time. However, a key limitation of such techniques is that they...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	343,810
2408.06698	High-order projection-based upwind method for simulation of transitional turbulent flows	We present a scalable, high-order implicit large-eddy simulation (ILES) approach for incompressible transitional flows. This method employs the mass-conserving mixed stress (MCS) method for discretizing the Navier-Stokes equations. The MCS method's low dissipation characteristics, combined with the introduced operator-...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	480,306
2007.15506	SimPose: Effectively Learning DensePose and Surface Normals of People from Simulated Data	With a proliferation of generic domain-adaptation approaches, we report a simple yet effective technique for learning difficult per-pixel 2.5D and 3D regression representations of articulated people. We obtained strong sim-to-real domain generalization for the 2.5D DensePose estimation task and the 3D human surface nor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	189,681
2009.00100	Online Multi-Object Tracking and Segmentation with GMPHD Filter and Mask-based Affinity Fusion	In this paper, we propose a highly practical fully online multi-object tracking and segmentation (MOTS) method that uses instance segmentation results as an input. The proposed method is based on the Gaussian mixture probability hypothesis density (GMPHD) filter, a hierarchical data association (HDA), and a mask-based ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	193,953
1905.10427	DIVA: Domain Invariant Variational Autoencoders	We consider the problem of domain generalization, namely, how to learn representations given data from a set of domains that generalize to data from a previously unseen domain. We propose the Domain Invariant Variational Autoencoder (DIVA), a generative model that tackles this problem by learning three independent late...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,053
1505.00511	Iterative Detection and Decoding Algorithms using LDPC Codes for MIMO Systems in Block-Fading Channels	We propose iterative detection and decoding (IDD) algorithms with Low-Density Parity-Check (LDPC) codes for Multiple Input Multiple Output (MIMO) systems operating in block-fading and fast Rayleigh fading channels. Soft-input soft-output minimum mean-square error receivers with successive interference cancellation are ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,738
2403.03483	A Teacher-Free Graph Knowledge Distillation Framework with Dual Self-Distillation	Recent years have witnessed great success in handling graph-related tasks with Graph Neural Networks (GNNs). Despite their great academic success, Multi-Layer Perceptrons (MLPs) remain the primary workhorse for practical industrial applications. One reason for such an academic-industry gap is the neighborhood-fetching ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	435,213
1810.10535	Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning	This paper presents a new meta-modeling framework to employ deep reinforcement learning (DRL) to generate mechanical constitutive models for interfaces. The constitutive models are conceptualized as information flow in directed graphs. The process of writing constitutive models are simplified as a sequence of forming g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,315
1906.07125	Replacing the do-calculus with Bayes rule	The concept of causality has a controversial history. The question of whether it is possible to represent and address causal problems with probability theory, or if fundamentally new mathematics such as the do calculus is required has been hotly debated, e.g. Pearl (2001) states "the building blocks of our scientific a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	135,513
1711.05561	A Stochastic Resource-Sharing Network for Electric Vehicle Charging	We consider a distribution grid used to charge electric vehicles such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control ru...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	84,600
2311.05221	Let's Get the FACS Straight -- Reconstructing Obstructed Facial Features	The human face is one of the most crucial parts in interhuman communication. Even when parts of the face are hidden or obstructed the underlying facial movements can be understood. Machine learning approaches often fail in that regard due to the complexity of the facial structures. To alleviate this problem a common ap...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	406,516
2202.10613	Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces	Bayesian learning using Gaussian processes provides a foundational framework for making decisions in a manner that balances what is known with what could be learned by gathering data. In this dissertation, we develop techniques for broadening the applicability of Gaussian processes. This is done in two ways. Firstly, w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	281,594
1512.02548	A Stabilised Nodal Spectral Element Method for Fully Nonlinear Water Waves	We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite element method proposed by Cai et al (1998) \cite{CaiEtAl1998}, although the nume...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	49,948
2404.13649	Distributional Principal Autoencoders	Dimension reduction techniques usually lose information in the sense that reconstructed data are not identical to the original data. However, we argue that it is possible to have reconstructed data identically distributed as the original data, irrespective of the retained dimension or the specific mapping. This can be ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	448,381
2407.09732	Speech Slytherin: Examining the Performance and Efficiency of Mamba for Speech Separation, Recognition, and Synthesis	It is too early to conclude that Mamba is a better alternative to transformers for speech before comparing Mamba with transformers in terms of both performance and efficiency in multiple speech-related tasks. To reach this conclusion, we propose and evaluate three models for three tasks: Mamba-TasNet for speech separat...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	472,699
1107.1128	AISMOTIF-An Artificial Immune System for DNA Motif Discovery	Discovery of transcription factor binding sites is a much explored and still exploring area of research in functional genomics. Many computational tools have been developed for finding motifs and each of them has their own advantages as well as disadvantages. Most of these algorithms need prior knowledge about the data...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	11,171
2311.06379	DeMuX: Data-efficient Multilingual Learning	We consider the task of optimally fine-tuning pre-trained multilingual models, given small amounts of unlabelled target data and an annotation budget. In this paper, we introduce DEMUX, a framework that prescribes the exact data-points to label from vast amounts of unlabelled multilingual data, having unknown degrees o...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	406,914
1904.07837	Predicting GNSS satellite visibility from dense point clouds	To help future mobile agents plan their movement in harsh environments,a predictive model has been designed to determine what areas would be favorable for Global Navigation Satellite System (GNSS) positioning. The model is able to predict the number of viable satellites for a GNSS receiver, based on a 3D point cloud ma...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	127,897
2307.09944	ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method	Capsule Networks have emerged as a powerful class of deep learning architectures, known for robust performance with relatively few parameters compared to Convolutional Neural Networks (CNNs). However, their inherent efficiency is often overshadowed by their slow, iterative routing mechanisms which establish connections...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	380,360
1901.00190	End-to-End Performance Optimization in Hybrid Molecular and Electromagnetic Communications	Telemedicine refers to the use of information and communication technology to assist with medical information and services. In health care applications, high reliable communication links between the health care provider and the desired destination in the human body play a central role in designing end-to-end (E2E) tele...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	117,713
1502.04617	Deep Transform: Error Correction via Probabilistic Re-Synthesis	Errors in data are usually unwelcome and so some means to correct them is useful. However, it is difficult to define, detect or correct errors in an unsupervised way. Here, we train a deep neural network to re-synthesize its inputs at its output layer for a given class of data. We then exploit the fact that this abstra...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	40,285
2401.10590	Adversarial Robustness of Link Sign Prediction in Signed Graphs	Signed graphs serve as fundamental data structures for representing positive and negative relationships in social networks, with signed graph neural networks (SGNNs) emerging as the primary tool for their analysis. Our investigation reveals that balance theory, while essential for modeling signed relationships in SGNNs...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	422,701
2010.03170	Modeling and Prediction of Rigid Body Motion with Planar Non-Convex Contact	We present a principled method for motion prediction via dynamic simulation for rigid bodies in intermittent contact with each other where the contact region is a planar non-convex contact patch. Such methods are useful in planning and control for robotic manipulation. The planar non-convex contact patch can either b...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	199,307
1504.01101	Private Data Transfer over a Broadcast Channel	We study the following private data transfer problem: Alice has a database of files. Bob and Cathy want to access a file each from this database (which may or may not be the same file), but each of them wants to ensure that their choices of file do not get revealed even if Alice colludes with the other user. Alice, on ...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	41,770

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.