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
2212.13398	Poseidon: Non-server WEB Forms Off-line Processing System	The proposed Poseidon system is based on email services of filled forms instead of WEB server based services. This approach is convenient especially for small applications or small-medium companies. It is based on PDF forms that are available on a WEB page. PDF forms can be downloaded, off-line filled in, printed and f...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	338,292
2204.11695	Estimation of Reliable Proposal Quality for Temporal Action Detection	Temporal action detection (TAD) aims to locate and recognize the actions in an untrimmed video. Anchor-free methods have made remarkable progress which mainly formulate TAD into two tasks: classification and localization using two separate branches. This paper reveals the temporal misalignment between the two tasks hin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,235
2004.14692	Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice	Given a CNF formula F on n variables, the problem of model counting or #SAT is to compute the number of satisfying assignments of F . Model counting is a fundamental but hard problem in computer science with varied applications. Recent years have witnessed a surge of effort towards developing efficient algorithmic tech...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	174,977
2410.05091	DIMS: Distributed Index for Similarity Search in Metric Spaces	Similarity search finds objects that are similar to a given query object based on a similarity metric. As the amount and variety of data continue to grow, similarity search in metric spaces has gained significant attention. Metric spaces can accommodate any type of data and support flexible distance metrics, making sim...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	495,562
1504.00253	Tables of the existence of equiangular tight frames	A Grassmannian frame is a collection of unit vectors which are optimally incoherent. To date, the vast majority of explicit Grassmannian frames are equiangular tight frames (ETFs). This paper surveys every known construction of ETFs and tabulates existence for sufficiently small dimensions.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,691
2205.03256	OROS: Online Operation and Orchestration of Collaborative Robots using 5G	The 5G mobile networks extend the capability for supporting collaborative robot operations in outdoor scenarios. However, the restricted battery life of robots still poses a major obstacle to their effective implementation and utilization in real scenarios. One of the most challenging situations is the execution of mis...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	295,225
1904.03787	Bayesian Non-Parametric Multi-Source Modelling Based Determined Blind Source Separation	This paper proposes a determined blind source separation method using Bayesian non-parametric modelling of sources. Conventionally source signals are separated from a given set of mixture signals by modelling them using non-negative matrix factorization (NMF). However in NMF, a latent variable signifying model complexi...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,835
2302.01524	Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing	Most graph neural networks follow the message passing mechanism. However, it faces the over-smoothing problem when multiple times of message passing is applied to a graph, causing indistinguishable node representations and prevents the model to effectively learn dependencies between farther-away nodes. On the other han...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,637
1706.03282	Segmentation of nearly isotropic overlapped tracks in photomicrographs using successive erosions as watershed markers	The major challenges of automatic track counting are distinguishing tracks and material defects, identifying small tracks and defects of similar size, and detecting overlapping tracks. Here we address the latter issue using WUSEM, an algorithm which combines the watershed transform, morphological erosions and labeling ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	75,136
1611.10182	Deriving a Generalized, Actuator Position-Independent Expression for the Force Output of a Scissor Lift	Scissor lifts, a staple of mechanical design, especially in competitive robotics, are a type of linkage that can be used to raise a load to some height, when acted upon by some force, usually exerted by an actuator. The position of this actuator, however, can affect the mechanical advantage and velocity ratio of the sy...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	64,784
1605.02147	Unified Error Rates Analysis of MIMO Space-Time Block Codes over Generalized Shadowed {\kappa}-{\mu} and {\eta}-{\mu} Fading and AWGGN	This paper presents a novel unified performance analysis of Space-Time Block Codes (STBCs) operating in the Multiple Input Multiple Output (MIMO) network and subjected to generalized shadowed fading and noise scenarios. Specifically, we derive novel, simple and accurate average bit error rates (ABER) expressions for co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,582
2303.09101	Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bank	Despite the remarkable achievement of recent underwater image restoration techniques, the lack of labeled data has become a major hurdle for further progress. In this work, we propose a mean-teacher based Semi-supervised Underwater Image Restoration (Semi-UIR) framework to incorporate the unlabeled data into network tr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,912
1810.00240	Reinforcement Learning in R	Reinforcement learning refers to a group of methods from artificial intelligence where an agent performs learning through trial and error. It differs from supervised learning, since reinforcement learning requires no explicit labels; instead, the agent interacts continuously with its environment. That is, the agent sta...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,131
2406.05630	Ctrl-V: Higher Fidelity Video Generation with Bounding-Box Controlled Object Motion	Controllable video generation has attracted significant attention, largely due to advances in video diffusion models. In domains such as autonomous driving, it is essential to develop highly accurate predictions for object motions. This paper tackles a crucial challenge of how to exert precise control over object motio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	462,220
2201.10227	Cold Start Active Learning Strategies in the Context of Imbalanced Classification	We present novel active learning strategies dedicated to providing a solution to the cold start stage, i.e. initializing the classification of a large set of data with no attached labels. Moreover, proposed strategies are designed to handle an imbalanced context in which random selection is highly inefficient. Specific...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	276,915
1310.0282	Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data	The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half million individuals and 370 cities to analyze the und...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	27,466
2004.05495	Learning to Manipulate Individual Objects in an Image	We describe a method to train a generative model with latent factors that are (approximately) independent and localized. This means that perturbing the latent variables affects only local regions of the synthesized image, corresponding to objects. Unlike other unsupervised generative models, ours enables object-centric...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	172,210
2102.03692	What's in a Name? -- Gender Classification of Names with Character Based Machine Learning Models	Gender information is no longer a mandatory input when registering for an account at many leading Internet companies. However, prediction of demographic information such as gender and age remains an important task, especially in intervention of unintentional gender/age bias in recommender systems. Therefore it is neces...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	218,833
2502.07866	Design and Implementation of Scalable Communication Interfaces for Reliable and Stable Real-time Co-Simulation of Power Systems	Co-simulation offers an integrated approach for modeling the large-scale integration of inverter-based resources (IBRs) into transmission and distribution grids. This paper presents a scalable communication interface design and implementation to enable reliable and stable real-time co-simulation of power systems with h...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	532,812
2211.00382	Seg&Struct: The Interplay Between Part Segmentation and Structure Inference for 3D Shape Parsing	We propose Seg&Struct, a supervised learning framework leveraging the interplay between part segmentation and structure inference and demonstrating their synergy in an integrated framework. Both part segmentation and structure inference have been extensively studied in the recent deep learning literature, while the sup...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	327,854
2302.07801	Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy	In recent years, diffusion models have achieved tremendous success in the field of image generation, becoming the stateof-the-art technology for AI-based image processing applications. Despite the numerous benefits brought by recent advances in diffusion models, there are also concerns about their potential misuse, spe...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	345,836
1702.05354	Algorithms for Online Influencer Marketing	Influence maximization is the problem of finding influential users, or nodes, in a graph so as to maximize the spread of information. It has many applications in advertising and marketing on social networks. In this paper, we study a highly generic version of influence maximization, one of optimizing influence campaign...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	68,384
2006.05621	Understanding Points of Correspondence between Sentences for Abstractive Summarization	Fusing sentences containing disparate content is a remarkable human ability that helps create informative and succinct summaries. Such a simple task for humans has remained challenging for modern abstractive summarizers, substantially restricting their applicability in real-world scenarios. In this paper, we present an...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	181,141
2108.11577	Machine Unlearning of Features and Labels	Removing information from a machine learning model is a non-trivial task that requires to partially revert the training process. This task is unavoidable when sensitive data, such as credit card numbers or passwords, accidentally enter the model and need to be removed afterwards. Recently, different concepts for machin...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	252,219
2110.04276	Offline Meta-Reinforcement Learning for Industrial Insertion	Reinforcement learning (RL) can in principle let robots automatically adapt to new tasks, but current RL methods require a large number of trials to accomplish this. In this paper, we tackle rapid adaptation to new tasks through the framework of meta-learning, which utilizes past tasks to learn to adapt with a specific...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	259,823
1901.07042	MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs	Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's thorax, but requiring specialized training for proper interpretation. With the advent of high performance general purpose computer vision algorithms, the accurate automated analysis of chest radiographs is bec...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	119,138
2405.13090	FedASTA: Federated adaptive spatial-temporal attention for traffic flow prediction	Mobile devices and the Internet of Things (IoT) devices nowadays generate a large amount of heterogeneous spatial-temporal data. It remains a challenging problem to model the spatial-temporal dynamics under privacy concern. Federated learning (FL) has been proposed as a framework to enable model training across distrib...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	455,805
1204.0166	Worst-Case Robust Multiuser Transmit Beamforming Using Semidefinite Relaxation: Duality and Implications	This paper studies a downlink multiuser transmit beamforming design under spherical channel uncertainties, using a worst-case robust formulation. This robust design problem is nonconvex. Recently, a convex approximation formulation based on semidefinite relaxation (SDR) has been proposed to handle the problem. Curiousl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	15,217
0911.3108	On game psychology: an experiment on the chess board/screen, should you always "do your best", and why the programs with prescribed weaknesses cannot be our good friends?	It is noted that some unusual moves against a strong chess program greatly weaken its ability to see the serious targets of the game, and its whole level of play... It is suggested to create programs with different weaknesses in order to analyze similar human behavior. Finally, a new version of chess, "Chess Corrida" i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	4,950
2208.06674	DS-MVSNet: Unsupervised Multi-view Stereo via Depth Synthesis	In recent years, supervised or unsupervised learning-based MVS methods achieved excellent performance compared with traditional methods. However, these methods only use the probability volume computed by cost volume regularization to predict reference depths and this manner cannot mine enough information from the proba...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	312,791
1903.05704	HopRank: How Semantic Structure Influences Teleportation in PageRank (A Case Study on BioPortal)	This paper introduces HopRank, an algorithm for modeling human navigation on semantic networks. HopRank leverages the assumption that users know or can see the whole structure of the network. Therefore, besides following links, they also follow nodes at certain distances (i.e., k-hop neighborhoods), and not at random a...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	124,214
2311.14773	Set Features for Anomaly Detection	This paper proposes to use set features for detecting anomalies in samples that consist of unusual combinations of normal elements. Many leading methods discover anomalies by detecting an unusual part of a sample. For example, state-of-the-art segmentation-based approaches, first classify each element of the sample (e....	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	410,257
1907.09955	Floating Displacement-Force Conversion Mechanism as a Robotic Mechanism	To attach and detach permanent magnets with an operation force smaller than their attractive force, Internally-Balanced Magnetic Unit (IB Magnet) has been developed. The unit utilizes a nonlinear spring with an inverse characteristic of magnetic attraction to produce a balancing force for canceling the internal force a...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	139,509
2405.19444	MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions	Large language models (LLMs) have demonstrated impressive capabilities in mathematical problem solving, particularly in single turn question answering formats. However, real world scenarios often involve mathematical question answering that requires multi turn or interactive information exchanges, and the performance o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	458,898
2406.07399	Redefining Automotive Radar Imaging: A Domain-Informed 1D Deep Learning Approach for High-Resolution and Efficient Performance	Millimeter-wave (mmWave) radars are indispensable for perception tasks of autonomous vehicles, thanks to their resilience in challenging weather conditions. Yet, their deployment is often limited by insufficient spatial resolution for precise semantic scene interpretation. Classical super-resolution techniques adapted ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	463,029
2003.00504	MonoPair: Monocular 3D Object Detection Using Pairwise Spatial Relationships	Monocular 3D object detection is an essential component in autonomous driving while challenging to solve, especially for those occluded samples which are only partially visible. Most detectors consider each 3D object as an independent training target, inevitably resulting in a lack of useful information for occluded sa...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	166,320
cs/0703049	Algorithm of Segment-Syllabic Synthesis in Speech Recognition Problem	Speech recognition based on the syllable segment is discussed in this paper. The principal search methods in space of states for the speech recognition problem by segment-syllabic parameters trajectory synthesis are investigated. Recognition as comparison the parameters trajectories in chosen speech units on the sectio...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	540,226
2006.09075	PERL: Pivot-based Domain Adaptation for Pre-trained Deep Contextualized Embedding Models	Pivot-based neural representation models have lead to significant progress in domain adaptation for NLP. However, previous works that follow this approach utilize only labeled data from the source domain and unlabeled data from the source and target domains, but neglect to incorporate massive unlabeled corpora that are...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	182,415
1705.07463	Spatially Controlled Relay Beamforming: $2$-Stage Optimal Policies	The problem of enhancing Quality-of-Service (QoS) in power constrained, mobile relay beamforming networks, by optimally and dynamically controlling the motion of the relaying nodes, is considered, in a dynamic channel environment. We assume a time slotted system, where the relays update their positions before the begin...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	73,844
1805.07071	Multi-level Wavelet-CNN for Image Restoration	The tradeoff between receptive field size and efficiency is a crucial issue in low level vision. Plain convolutional networks (CNNs) generally enlarge the receptive field at the expense of computational cost. Recently, dilated filtering has been adopted to address this issue. But it suffers from gridding effect, and th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	97,736
2211.02612	Reservoir Computing via Quantum Recurrent Neural Networks	Recent developments in quantum computing and machine learning have propelled the interdisciplinary study of quantum machine learning. Sequential modeling is an important task with high scientific and commercial value. Existing VQC or QNN-based methods require significant computational resources to perform the gradient-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	328,628
2402.13534	An Effective Incorporating Heterogeneous Knowledge Curriculum Learning for Sequence Labeling	Sequence labeling models often benefit from incorporating external knowledge. However, this practice introduces data heterogeneity and complicates the model with additional modules, leading to increased expenses for training a high-performing model. To address this challenge, we propose a two-stage curriculum learning ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	431,295
2008.13024	Dual Attention GANs for Semantic Image Synthesis	In this paper, we focus on the semantic image synthesis task that aims at transferring semantic label maps to photo-realistic images. Existing methods lack effective semantic constraints to preserve the semantic information and ignore the structural correlations in both spatial and channel dimensions, leading to unsati...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	193,741
2304.13226	Cooperative Hierarchical Deep Reinforcement Learning based Joint Sleep and Power Control in RIS-aided Energy-Efficient RAN	Energy efficiency (EE) is one of the most important metrics for envisioned 6G networks, and sleep control, as a cost-efficient approach, can significantly lower power consumption by switching off network devices selectively. Meanwhile, the reconfigurable intelligent surface (RIS) has emerged as a promising technique to...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	360,511
2104.11884	Social Distancing via Social Scheduling	Motivated by the need of {\em social distancing} during a pandemic, we consider an approach to schedule the visitors of a facility (e.g., a general store). Our algorithms take input from the citizens and schedule the store's discrete time-slots based on their importance to visit the facility. Naturally, the formulation...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	232,046
1911.04283	Data Efficient Direct Speech-to-Text Translation with Modality Agnostic Meta-Learning	End-to-end Speech Translation (ST) models have several advantages such as lower latency, smaller model size, and less error compounding over conventional pipelines that combine Automatic Speech Recognition (ASR) and text Machine Translation (MT) models. However, collecting large amounts of parallel data for ST task is ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	152,950
1612.08479	Social contagion with degree-dependent thresholds	We investigate opinion spreading by a threshold model in a situation where the influence of people is heterogeneously distributed. We focus on the response of the average opinion as a function between the trend between out-degree (number of neighbors)---effectively the strength of influence of a node---and the threshol...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	66,078
1906.00890	Stability of Open Multi-Agent Systems and Applications to Dynamic Consensus	In this technical note we consider a class of multi-agent network systems that we refer to as Open Multi-Agent Systems (OMAS): in these multi-agent systems, an indefinite number of agents may join or leave the network at any time. Focusing on discrete-time evolutions of scalar agents, we provide a novel theoretical fra...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	133,534
2204.10413	Staying the course: Locating equilibria of dynamical systems on Riemannian manifolds defined by point-clouds	We introduce a method to successively locate equilibria (steady states) of dynamical systems on Riemannian manifolds. The manifolds need not be characterized by an a priori known atlas or by the zeros of a smooth map. Instead, they can be defined by point-clouds and sampled as needed through an iterative process. If th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	292,771
1404.3538	Proceedings of The 38th Annual Workshop of the Austrian Association for Pattern Recognition (\"OAGM), 2014	The 38th Annual Workshop of the Austrian Association for Pattern Recognition (\"OAGM) will be held at IST Austria, on May 22-23, 2014. The workshop provides a platform for researchers and industry to discuss traditional and new areas of computer vision. This year the main topic is: Pattern Recognition: interdisciplinar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	32,319
2211.08650	Deep Intention-Aware Network for Click-Through Rate Prediction	E-commerce platforms provide entrances for customers to enter mini-apps that can meet their specific shopping requirements. Trigger items displayed on entrance icons can attract more entering. However, conventional Click-Through-Rate (CTR) prediction models, which ignore user instant interest in trigger item, fail to b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	330,712
2110.15023	Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC	Machine translation (MT) system aims to translate source language into target language. Recent studies on MT systems mainly focus on neural machine translation (NMT). One factor that significantly affects the performance of NMT is the availability of high-quality parallel corpora. However, high-quality parallel corpora...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	263,728
1507.05722	A Review of Network Traffic Analysis and Prediction Techniques	Analysis and prediction of network traffic has applications in wide comprehensive set of areas and has newly attracted significant number of studies. Different kinds of experiments are conducted and summarized to identify various problems in existing computer network applications. Network traffic analysis and predictio...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	45,317
2006.11511	Improving Query Safety at Pinterest	Query recommendations in search engines is a double edged sword, with undeniable benefits but potential of harm. Identifying unsafe queries is necessary to protect users from inappropriate query suggestions. However, identifying these is non-trivial because of the linguistic diversity resulting from large vocabularies,...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	183,266
2309.11988	Relaxed Conditions for Parameterized Linear Matrix Inequality in the Form of Nested Fuzzy Summations	The aim of this study is to investigate less conservative conditions for parameterized linear matrix inequalities (PLMIs) that are formulated as nested fuzzy summations. Such PLMIs are commonly encountered in stability analysis and control design problems for Takagi-Sugeno (T-S) fuzzy systems. Utilizing the weighted in...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	393,619
1507.08199	On the Digital Daily Cycles of Individuals	Humans, like almost all animals, are phase-locked to the diurnal cycle. Most of us sleep at night and are active through the day. Because we have evolved to function with this cycle, the circadian rhythm is deeply ingrained and even detectable at the biochemical level. However, within the broader day-night pattern, the...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	45,546
2110.13244	DeepHelp: Deep Learning for Shout Crisis Text Conversations	The Shout Crisis Text Line provides individuals undergoing mental health crises an opportunity to have an anonymous text message conversation with a trained Crisis Volunteer (CV). This project partners with Shout and its parent organisation, Mental Health Innovations, to explore the applications of Machine Learning in ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	263,108
1911.07953	Sequential Multi-Frame Neural Beamforming for Speech Separation and Enhancement	This work introduces sequential neural beamforming, which alternates between neural network based spectral separation and beamforming based spatial separation. Our neural networks for separation use an advanced convolutional architecture trained with a novel stabilized signal-to-noise ratio loss function. For beamformi...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	154,026
2206.06109	Markov Decision Processes under Model Uncertainty	We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting. By providing a dynamic programming principle we obtain a local-to-global paradigm, namely solving a local, i.e., a one time-step robust optimization problem leads to an optimizer of the glo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,255
2203.14899	Properties and Performance of the ABCDe Random Graph Model with Community Structure	In this paper, we investigate properties and performance of synthetic random graph models with a built-in community structure. Such models are important for evaluating and tuning community detection algorithms that are unsupervised by nature. We propose ABCDe, a multi-threaded implementation of the ABCD (Artificial Ben...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	288,166
2211.16444	Holding AI to Account: Challenges for the Delivery of Trustworthy AI in Healthcare	The need for AI systems to provide explanations for their behaviour is now widely recognised as key to their adoption. In this paper, we examine the problem of trustworthy AI and explore what delivering this means in practice, with a focus on healthcare applications. Work in this area typically treats trustworthy AI as...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	333,635
2502.07239	Contextual Gesture: Co-Speech Gesture Video Generation through Context-aware Gesture Representation	Co-speech gesture generation is crucial for creating lifelike avatars and enhancing human-computer interactions by synchronizing gestures with speech. Despite recent advancements, existing methods struggle with accurately identifying the rhythmic or semantic triggers from audio for generating contextualized gesture pat...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	532,502
2012.08407	Multi-Aspect Sentiment Analysis with Latent Sentiment-Aspect Attribution	In this paper, we introduce a new framework called the sentiment-aspect attribution module (SAAM). SAAM works on top of traditional neural networks and is designed to address the problem of multi-aspect sentiment classification and sentiment regression. The framework works by exploiting the correlations between sentenc...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	211,757
1507.05497	RAPS: A Recommender Algorithm Based on Pattern Structures	We propose a new algorithm for recommender systems with numeric ratings which is based on Pattern Structures (RAPS). As the input the algorithm takes rating matrix, e.g., such that it contains movies rated by users. For a target user, the algorithm returns a rated list of items (movies) based on its previous ratings an...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	true	45,294
2202.02860	MIMO Systems with One-bit ADCs: Capacity Gains using Nonlinear Analog Operations	Analog to Digital Converters (ADCs) are a major contributor to the energy consumption on the receiver side of millimeter-wave multiple-input multiple-output (MIMO) systems with large antenna arrays. Consequently, there has been significant interest in using low-resolution ADCs along with hybrid beam-forming at MIMO rec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	278,975
1709.00023	R$^3$: Reinforced Reader-Ranker for Open-Domain Question Answering	In recent years researchers have achieved considerable success applying neural network methods to question answering (QA). These approaches have achieved state of the art results in simplified closed-domain settings such as the SQuAD (Rajpurkar et al., 2016) dataset, which provides a pre-selected passage, from which th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	79,836
1902.05690	AutoQ: Automated Kernel-Wise Neural Network Quantization	Network quantization is one of the most hardware friendly techniques to enable the deployment of convolutional neural networks (CNNs) on low-power mobile devices. Recent network quantization techniques quantize each weight kernel in a convolutional layer independently for higher inference accuracy, since the weight ker...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	121,605
2501.12588	Fundamental Limits of Non-Adaptive Group Testing with Markovian Correlation	We study a correlated group testing model where items are infected according to a Markov chain, which creates bursty binfection patterns. Focusing on a very sparse infections regime, we propose a non adaptive testing strategy with an efficient decoding scheme that is nearly optimal. Specifically, it achieves asymptotic...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	526,367
1803.09263	P2P-NET: Bidirectional Point Displacement Net for Shape Transform	We introduce P2P-NET, a general-purpose deep neural network which learns geometric transformations between point-based shape representations from two domains, e.g., meso-skeletons and surfaces, partial and complete scans, etc. The architecture of the P2P-NET is that of a bi-directional point displacement network, which...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	93,464
1212.2390	On the complexity of learning a language: An improvement of Block's algorithm	Language learning is thought to be a highly complex process. One of the hurdles in learning a language is to learn the rules of syntax of the language. Rules of syntax are often ordered in that before one rule can applied one must apply another. It has been thought that to learn the order of n rules one must go through...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	20,244
2406.07811	Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems	Artificial intelligence methods are being increasingly applied across various domains, but their often opaque nature has raised concerns about accountability and trust. In response, the field of explainable AI (XAI) has emerged to address the need for human-understandable AI systems. Evolutionary computation (EC), a fa...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	463,216
2112.08817	Search for temporal cell segmentation robustness in phase-contrast microscopy videos	Studying cell morphology changes in time is critical to understanding cell migration mechanisms. In this work, we present a deep learning-based workflow to segment cancer cells embedded in 3D collagen matrices and imaged with phase-contrast microscopy. Our approach uses transfer learning and recurrent convolutional lon...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	271,950
2110.06006	Robust Glare Detection: Review, Analysis, and Dataset Release	Sun Glare widely exists in the images captured by unmanned ground and aerial vehicles performing in outdoor environments. The existence of such artifacts in images will result in wrong feature extraction and failure of autonomous systems. Humans will try to adapt their view once they observe a glare (especially when dr...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	260,471
2012.06036	Data-based Discovery of Governing Equations	Most common mechanistic models are traditionally presented in mathematical forms to explain a given physical phenomenon. Machine learning algorithms, on the other hand, provide a mechanism to map the input data to output without explicitly describing the underlying physical process that generated the data. We propose a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	210,969
2410.11216	Experiences from Creating a Benchmark for Sentiment Classification for Varieties of English	Existing benchmarks often fail to account for linguistic diversity, like language variants of English. In this paper, we share our experiences from our ongoing project of building a sentiment classification benchmark for three variants of English: Australian (en-AU), Indian (en-IN), and British (en-UK) English. Using G...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	498,442
2203.15793	Instance Relation Graph Guided Source-Free Domain Adaptive Object Detection	Unsupervised Domain Adaptation (UDA) is an effective approach to tackle the issue of domain shift. Specifically, UDA methods try to align the source and target representations to improve the generalization on the target domain. Further, UDA methods work under the assumption that the source data is accessible during the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	288,540
2109.07570	Predicting the outcome of team movements -- Player time series analysis using fuzzy and deep methods for representation learning	We extract and use player position time-series data, tagged along with the action types, to build a competent model for representing team tactics behavioral patterns and use this representation to predict the outcome of arbitrary movements. We provide a framework for the useful encoding of short tactics and space occup...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	255,566
2410.00145	Constraint-Aware Refinement for Safety Verification of Neural Feedback Loops	Neural networks (NNs) are becoming increasingly popular in the design of control pipelines for autonomous systems. However, since the performance of NNs can degrade in the presence of out-of-distribution data or adversarial attacks, systems that have NNs in their control pipelines, i.e., neural feedback loops (NFLs), n...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	493,243
1612.05710	Multi-modal Mining and Modeling of Big Mobile Networks Based on Users Behavior and Interest	Usage of mobile wireless Internet has grown very fast in recent years. This radical change in availability of Internet has led to communication of big amount of data over mobile networks and consequently new challenges and opportunities for modeling of mobile Internet characteristics. While the traditional approach tow...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	65,715
2406.09825	Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System Telemetry	The detection of abnormal or critical system states is essential in condition monitoring. While much attention is given to promptly identifying anomalies, a retrospective analysis of these anomalies can significantly enhance our comprehension of the underlying causes of observed undesired behavior. This aspect becomes ...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	464,099
1210.6095	Interference Coordination: Random Clustering and Adaptive Limited Feedback	Interference coordination improves data rates and reduces outages in cellular networks. Accurately evaluating the gains of coordination, however, is contingent upon using a network topology that models realistic cellular deployments. In this paper, we model the base stations locations as a Poisson point process to prov...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,336
1406.5670	3D ShapeNets: A Deep Representation for Volumetric Shapes	3D shape is a crucial but heavily underutilized cue in today's computer vision systems, mostly due to the lack of a good generic shape representation. With the recent availability of inexpensive 2.5D depth sensors (e.g. Microsoft Kinect), it is becoming increasingly important to have a powerful 3D shape representation ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	34,049
2308.00353	Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding	Open-world instance-level scene understanding aims to locate and recognize unseen object categories that are not present in the annotated dataset. This task is challenging because the model needs to both localize novel 3D objects and infer their semantic categories. A key factor for the recent progress in 2D open-world...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	382,913
1803.07980	Information Theoretic Interpretation of Deep learning	We interpret part of the experimental results of Shwartz-Ziv and Tishby [2017]. Inspired by these results, we established a conjecture of the dynamics of the machinary of deep neural network. This conjecture can be used to explain the counterpart result by Saxe et al. [2018].	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	93,170
2303.17093	OpenMix: Exploring Outlier Samples for Misclassification Detection	Reliable confidence estimation for deep neural classifiers is a challenging yet fundamental requirement in high-stakes applications. Unfortunately, modern deep neural networks are often overconfident for their erroneous predictions. In this work, we exploit the easily available outlier samples, i.e., unlabeled samples ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	355,103
2406.02745	Measuring Stochastic Data Complexity with Boltzmann Influence Functions	Estimating the uncertainty of a model's prediction on a test point is a crucial part of ensuring reliability and calibration under distribution shifts. A minimum description length approach to this problem uses the predictive normalized maximum likelihood (pNML) distribution, which considers every possible label for a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	460,916
2112.03084	ZeroMat: Solving Cold-start Problem of Recommender System with No Input Data	Recommender system is an applicable technique in most E-commerce commercial product technical designs. However, nearly all recommender system faces a challenge called the cold-start problem. The problem is so notorious that almost every industrial practitioner needs to resolve this issue when building recommender syste...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	270,076
2001.07627	batchboost: regularization for stabilizing training with resistance to underfitting & overfitting	Overfitting & underfitting and stable training are an important challenges in machine learning. Current approaches for these issues are mixup, SamplePairing and BC learning. In our work, we state the hypothesis that mixing many images together can be more effective than just two. Batchboost pipeline has three stages: (...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	161,089
1505.07278	Higher weight distribution of linearized Reed-Solomon codes	Linearized Reed-Solomon codes are defined. Higher weight distribution of those codes are determined.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	43,530
0804.4753	Wavelet Based Iterative Learning Control with Fuzzy PD Feedback for Position Tracking of A Pneumatic Servo System	In this paper, a wavelet-based iterative learning control (WILC) scheme with Fuzzy PD feedback is presented for a pneumatic control system with nonsmooth nonlinearities and uncertain parameters. The wavelet transform is employed to extract the learnable dynamics from measured output signal before it can be used to upda...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	1,673
1912.11252	Meta-Learning PAC-Bayes Priors in Model Averaging	Nowadays model uncertainty has become one of the most important problems in both academia and industry. In this paper, we mainly consider the scenario in which we have a common model set used for model averaging instead of selecting a single final model via a model selection procedure to account for this model's uncert...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	158,524
2403.12082	The Boy Who Survived: Removing Harry Potter from an LLM is harder than reported	Recent work arXiv.2310.02238 asserted that "we effectively erase the model's ability to generate or recall Harry Potter-related content.'' This claim is shown to be overbroad. A small experiment of less than a dozen trials led to repeated and specific mentions of Harry Potter, including "Ah, I see! A "muggle" is a term...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	439,027
2307.07597	Power consumption prediction for steel industry	The use of steel is essential in many industries, including infrastructure, transportation, and modern architecture. Predicting power consumption in the steel industry is crucial to meet the rising demand for steel and promoting city development. However, predicting energy consumption in the steel industry is challengi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	379,466
1804.10159	AbuSniff: Automatic Detection and Defenses Against Abusive Facebook Friends	Adversaries leverage social network friend relationships to collect sensitive data from users and target them with abuse that includes fake news, cyberbullying, malware, and propaganda. Case in point, 71 out of 80 user study participants had at least 1 Facebook friend with whom they never interact, either in Facebook o...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	96,101
2205.08935	Deep Features for CBIR with Scarce Data using Hebbian Learning	Features extracted from Deep Neural Networks (DNNs) have proven to be very effective in the context of Content Based Image Retrieval (CBIR). In recent work, biologically inspired \textit{Hebbian} learning algorithms have shown promises for DNN training. In this contribution, we study the performance of such algorithms ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	297,100
2212.09844	Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding	Predictive algorithms inform consequential decisions in settings where the outcome is selectively observed given choices made by human decision makers. We propose a unified framework for the robust design and evaluation of predictive algorithms in selectively observed data. We impose general assumptions on how much the...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	337,230
2105.01244	Regret-Optimal LQR Control	We consider the infinite-horizon LQR control problem. Motivated by competitive analysis in online learning, as a criterion for controller design we introduce the dynamic regret, defined as the difference between the LQR cost of a causal controller (that has only access to past disturbances) and the LQR cost of the \emp...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	233,467
2205.06666	The Case for a Legal Compliance API for the Enforcement of the EU's Digital Services Act on Social Media Platforms	In the course of under a year, the European Commission has launched some of the most important regulatory proposals to date on platform governance. The Commission's goals behind cross-sectoral regulation of this sort include the protection of markets and democracies alike. While all these acts propose sophisticated rul...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	296,308
2210.06801	Robust offset-free nonlinear model predictive control for systems learned by neural nonlinear autoregressive exogenous models	This paper presents a robust Model Predictive Control (MPC) scheme that provides offset-free setpoint tracking for systems described by Neural Nonlinear AutoRegressive eXogenous (NNARX) models. The NNARX model learns the dynamics of the plant from input-output data, and during the training the Incremental Input-to-Stat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	323,454
2106.09110	Safe Reinforcement Learning Using Advantage-Based Intervention	Many sequential decision problems involve finding a policy that maximizes total reward while obeying safety constraints. Although much recent research has focused on the development of safe reinforcement learning (RL) algorithms that produce a safe policy after training, ensuring safety during training as well remains ...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	241,541

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