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
2402.01262	Class incremental learning with probability dampening and cascaded gated classifier	Humans are capable of acquiring new knowledge and transferring learned knowledge into different domains, incurring a small forgetting. The same ability, called Continual Learning, is challenging to achieve when operating with neural networks due to the forgetting affecting past learned tasks when learning new ones. Thi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	425,940
1602.07106	Scalable Generation of Scale-free Graphs	We explain how massive instances of scale-free graphs following the Barabasi-Albert model can be generated very quickly in an embarrassingly parallel way. This makes this popular model available for studying big data graph problems. As a demonstration, we generated a Petaedge graph in less than an hour.	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	52,467
1604.04021	Beamforming for Simultaneous Wireless Information and Power Transfer in Two-Way Relay Channels	This paper studies simultaneous wireless information and power transfer (SWIPT) systems in two-way relaying (TWR) channels. Here, two source nodes receive information and energy simultaneously via power splitting (PS) from the signals sent by a multi-antenna relay node. Our objective is to maximize the weighted sum of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	54,587
2001.07135	Model Reuse with Reduced Kernel Mean Embedding Specification	Given a publicly available pool of machine learning models constructed for various tasks, when a user plans to build a model for her own machine learning application, is it possible to build upon models in the pool such that the previous efforts on these existing models can be reused rather than starting from scratch? ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,973
1309.1812	Cactus: Issues for Sustainable Simulation Software	The Cactus Framework is an open-source, modular, portable programming environment for the collaborative development and deployment of scientific applications using high-performance computing. Its roots reach back to 1996 at the National Center for Supercomputer Applications and the Albert Einstein Institute in Germany,...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	26,897
1902.08314	The NIGENS General Sound Events Database	Computational auditory scene analysis is gaining interest in the last years. Trailing behind the more mature field of speech recognition, it is particularly general sound event detection that is attracting increasing attention. Crucial for training and testing reasonable models is having available enough suitable data ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	122,166
2109.08815	Probabilistic Inference of Simulation Parameters via Parallel Differentiable Simulation	To accurately reproduce measurements from the real world, simulators need to have an adequate model of the physical system and require the parameters of the model be identified. We address the latter problem of estimating parameters through a Bayesian inference approach that approximates a posterior distribution over...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	256,027
2401.04820	Phishing Website Detection through Multi-Model Analysis of HTML Content	The way we communicate and work has changed significantly with the rise of the Internet. While it has opened up new opportunities, it has also brought about an increase in cyber threats. One common and serious threat is phishing, where cybercriminals employ deceptive methods to steal sensitive information.This study ad...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	420,546
2401.03901	STAIR: Spatial-Temporal Reasoning with Auditable Intermediate Results for Video Question Answering	Recently we have witnessed the rapid development of video question answering models. However, most models can only handle simple videos in terms of temporal reasoning, and their performance tends to drop when answering temporal-reasoning questions on long and informative videos. To tackle this problem we propose STAIR,...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	420,265
2401.14633	Semantic Arithmetic Coding using Synonymous Mappings	Recent semantic communication methods explore effective ways to expand the communication paradigm and improve the system performance of the communication systems. Nonetheless, the common problem of these methods is that the essence of semantics is not explicitly pointed out and directly utilized. A new epistemology sug...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	424,166
2310.05737	Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation	While Large Language Models (LLMs) are the dominant models for generative tasks in language, they do not perform as well as diffusion models on image and video generation. To effectively use LLMs for visual generation, one crucial component is the visual tokenizer that maps pixel-space inputs to discrete tokens appropr...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	398,273
1712.02552	Optimal Power Management for Failure Mode of MVDC Microgrids in All-Electric Ships	Optimal power management of shipboard power system for failure mode (OPMSF) is a significant and challenging problem considering the safety of system and person. Many existing works focused on the transient-time recovery without consideration of the operating cost and the voyage plan. In this paper, the OPMSF problem i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	86,312
1505.02002	The Key Elements of Viral Advertising. From Motivation to Emotion in the Most Shared Videos	From its origins in the mid 90s, the application of the concept of virality to commercial communication has represented an opportunity for brands to cross the traditional barriers of the audience concerning advertising and turn it into active communicator of brand messages. Viral marketing is based, since then, on two ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	42,911
2112.14822	UCoDe: Unified Community Detection with Graph Convolutional Networks	Community detection finds homogeneous groups of nodes in a graph. Existing approaches either partition the graph into disjoint, non-overlapping, communities, or determine only overlapping communities. To date, no method supports both detections of overlapping and non-overlapping communities. We propose UCoDe, a unified...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	273,621
2106.00599	ClustML: A Measure of Cluster Pattern Complexity in Scatterplots Learnt from Human-labeled Groupings	Visual quality measures (VQMs) are designed to support analysts by automatically detecting and quantifying patterns in visualizations. We propose a new VQM for visual grouping patterns in scatterplots, called ClustML, which is trained on previously collected human subject judgments. Our model encodes scatterplots in th...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	238,185
2305.02832	Comparison of retinal regions-of-interest imaged by OCT for the classification of intermediate AMD	To study whether it is possible to differentiate intermediate age-related macular degeneration (AMD) from healthy controls using partial optical coherence tomography (OCT) data, that is, restricting the input B-scans to certain pre-defined regions of interest (ROIs). A total of 15744 B-scans from 269 intermediate AMD p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	362,190
2409.14880	End-to-End Graph Flattening Method for Large Language Models	In recent years, the breakthrough of Large Language Models (LLMs) offers new ideas for achieving universal methods on graph data. The common practice of converting graphs into natural language for LLMs, which refers to graph flattening, exhibits good generalizability and interpretability. However, the poor organization...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	490,673
2501.14720	Communication-Based Distributed Control of Large-Scale District Heating Networks	This paper presents a non-cooperative distributed model predictive controller for the control of large-scale District Heating Networks. To enable the design of this controller a novel information passing scheme and feasibility restoration method are created, allowing the local controllers to achieve a global consensus ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	527,231
2109.10777	Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images	We propose a Deep Variational Clustering (DVC) framework for unsupervised representation learning and clustering of large-scale medical images. DVC simultaneously learns the multivariate Gaussian posterior through the probabilistic convolutional encoder and the likelihood distribution with the probabilistic convolution...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	256,745
2411.12335	Cities beyond proximity	The concept of `proximity-based cities' has gained attention as a new urban organizational model. Most prominently, the 15-minute city contends that cities can function more effectively, equitably and sustainably if essential, everyday services and key amenities are within a 15-minute walk or cycle. However, focusing s...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	509,386
1606.00151	Mapping and Localization from Planar Markers	Squared planar markers are a popular tool for fast, accurate and robust camera localization, but its use is frequently limited to a single marker, or at most, to a small set of them for which their relative pose is known beforehand. Mapping and localization from a large set of planar markers is yet a scarcely treated p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	56,637
1912.07259	PolSF: PolSAR image dataset on San Francisco	Polarimetric SAR data has the characteristics of all-weather, all-time and so on, which is widely used in many fields. However, the data of annotation is relatively small, which is not conducive to our research. In this paper, we have collected five open polarimetric SAR images, which are images of the San Francisco ar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,563
1704.06209	ADMM Penalty Parameter Selection by Residual Balancing	Appropriate selection of the penalty parameter is crucial to obtaining good performance from the Alternating Direction Method of Multipliers (ADMM). While analytic results for optimal selection of this parameter are very limited, there is a heuristic method that appears to be relatively successful in a number of differ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	72,139
2107.01138	Dissipativity-based static output feedback design for discrete-time LTI systems with time-varying input delays	This note is concerned with the presentation of new delay-dependent dissipativity-based convex conditions (expressed in the form of linear matrix inequalities) for the design of static output feedback (SOF) stabilizing gains for open-loop unstable discrete-time systems with input time-varying delays. A modified definit...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	244,382
2306.12508	Polynomial Logical Zonotope: A Set Representation for Reachability Analysis of Logical Systems	In this paper, we introduce a set representation called polynomial logical zonotopes for performing exact and computationally efficient reachability analysis on logical systems. We prove that through this polynomial-like construction, we are able to perform all of the fundamental logical operations (XOR, NOT, XNOR, AND...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	374,959
2303.11306	Localizing Object-level Shape Variations with Text-to-Image Diffusion Models	Text-to-image models give rise to workflows which often begin with an exploration step, where users sift through a large collection of generated images. The global nature of the text-to-image generation process prevents users from narrowing their exploration to a particular object in the image. In this paper, we presen...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	352,794
1712.09558	Memory-Efficient Deep Salient Object Segmentation Networks on Gridized Superpixels	Computer vision algorithms with pixel-wise labeling tasks, such as semantic segmentation and salient object detection, have gone through a significant accuracy increase with the incorporation of deep learning. Deep segmentation methods slightly modify and fine-tune pre-trained networks that have hundreds of millions of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	87,375
2106.05920	Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter	Text recognition is a popular research subject with many associated challenges. Despite the considerable progress made in recent years, the text recognition task itself is still constrained to solve the problem of reading cropped line text images and serves as a subtask of optical character recognition (OCR) systems. A...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	240,277
2210.14627	Channel-Aware Ordered Successive Relaying with Finite-Blocklength Coding	Successive relaying can improve the transmission rate by allowing the source and relays to transmit messages simultaneously, but it may cause severe inter-relay interference (IRI). IRI cancellation schemes have been proposed to mitigate IRI. However, interference cancellation methods have a high risk of error propagati...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	326,628
2109.13201	A 3-DoF Robotic Platform for the Rehabilitation and Assessment of Reaction Time and Balance Skills of MS Patients	The central nervous system exploits anticipatory (APAs) and compensatory (CPAs) postural adjustments to maintain the balance.The postural adjustments comprising stability of the center of mass (CoM) and the pressure distribution of the body influence each other if there is a lack of performance in either of them.Any pr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	257,562
2409.00896	A Noise and Edge extraction-based dual-branch method for Shallowfake and Deepfake Localization	The trustworthiness of multimedia is being increasingly evaluated by advanced Image Manipulation Localization (IML) techniques, resulting in the emergence of the IML field. An effective manipulation model necessitates the extraction of non-semantic differential features between manipulated and legitimate sections to ut...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,122
2310.10613	Stabilization of uncertain linear distributed delay systems with dissipativity constraints	This paper examines the problem of stabilizing linear distributed delay systems with nonlinear distributed delay kernels and dissipativity constraints. Specifically, the nonlinear distributed kernel includes functions such as polynomials, trigonometric and exponential functions. By constructing a Liapunov-Krasovski\v{i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	400,301
2201.12484	Fair Stable Matching Meets Correlated Preferences	The stable matching problem sets the economic foundation of several practical applications ranging from school choice and medical residency to ridesharing and refugee placement. It is concerned with finding a matching between two disjoint sets of agents wherein no pair of agents prefer each other to their matched partn...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	277,658
1311.6934	Image forgery detection based on the fusion of machine learning and block-matching methods	Dense local descriptors and machine learning have been used with success in several applications, like classification of textures, steganalysis, and forgery detection. We develop a new image forgery detector building upon some descriptors recently proposed in the steganalysis field suitably merging some of such descrip...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	28,702
2007.07012	A Weakly Supervised Region-Based Active Learning Method for COVID-19 Segmentation in CT Images	One of the key challenges in the battle against the Coronavirus (COVID-19) pandemic is to detect and quantify the severity of the disease in a timely manner. Computed tomographies (CT) of the lungs are effective for assessing the state of the infection. Unfortunately, labeling CT scans can take a lot of time and effort...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	187,200
2401.05650	On Context-aware Detection of Cherry-picking in News Reporting	Cherry-picking refers to the deliberate selection of evidence or facts that favor a particular viewpoint while ignoring or distorting evidence that supports an opposing perspective. Manually identifying cherry-picked statements in news stories can be challenging. In this study, we introduce a novel approach to detectin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	420,861
0811.4403	Joint Adaptive Modulation Coding and Cooperative ARQ over Relay Channels-Applications to Land Mobile Satellite Communications	In a cooperative relay network, a relay node (R) facilitates data transmission to the destination node (D), when the latter is unable to decode the source node (S) data correctly. This paper considers such a system model and presents a cross-layer approach to jointly design adaptive modulation and coding (AMC) at the p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,709
2207.00697	Superdirective Antenna Pairs for Energy-Efficient Terahertz Massive MIMO	Terahertz (THz) communication is widely deemed the next frontier of wireless networks owing to the abundant spectrum resources in the THz band. Whilst THz signals suffer from severe propagation losses, a massive antenna array can be deployed at the base station (BS) to mitigate those losses through beamforming. Neverth...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	305,849
2502.04728	Generating Symbolic World Models via Test-time Scaling of Large Language Models	Solving complex planning problems requires Large Language Models (LLMs) to explicitly model the state transition to avoid rule violations, comply with constraints, and ensure optimality-a task hindered by the inherent ambiguity of natural language. To overcome such ambiguity, Planning Domain Definition Language (PDDL) ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	531,294
2010.09714	A Convenient Generalization of Schlick's Bias and Gain Functions	We present a generalization of Schlick's bias and gain functions -- simple parametric curve-shaped functions for inputs in [0, 1]. Our single function includes both bias and gain as special cases, and is able to describe other smooth and monotonic curves with variable degrees of asymmetry.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	201,649
2002.11226	Deep Learning and Statistical Models for Time-Critical Pedestrian Behaviour Prediction	The time it takes for a classifier to make an accurate prediction can be crucial in many behaviour recognition problems. For example, an autonomous vehicle should detect hazardous pedestrian behaviour early enough for it to take appropriate measures. In this context, we compare the switching linear dynamical system (SL...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	165,642
1905.09904	CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation	Many real-world applications involve multivariate, geo-tagged time series data: at each location, multiple sensors record corresponding measurements. For example, air quality monitoring system records PM2.5, CO, etc. The resulting time-series data often has missing values due to device outages or communication errors. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	131,874
2104.04689	ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parser	Given a database schema, Text-to-SQL aims to translate a natural language question into the corresponding SQL query. Under the setup of cross-domain, traditional semantic parsing models struggle to adapt to unseen database schemas. To improve the model generalization capability for rare and unseen schemas, we propose a...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	229,460
1205.5980	Performance of polar codes for quantum and private classical communication	We analyze the practical performance of quantum polar codes, by computing rigorous bounds on block error probability and by numerically simulating them. We evaluate our bounds for quantum erasure channels with coding block lengths between 2^10 and 2^20, and we report the results of simulations for quantum erasure chann...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,198
1905.01273	Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images	Food computing is playing an increasingly important role in human daily life, and has found tremendous applications in guiding human behavior towards smart food consumption and healthy lifestyle. An important task under the food-computing umbrella is retrieval, which is particularly helpful for health related applicati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	129,678
2001.05862	An Investigation of Feature-based Nonrigid Image Registration using Gaussian Process	For a wide range of clinical applications, such as adaptive treatment planning or intraoperative image update, feature-based deformable registration (FDR) approaches are widely employed because of their simplicity and low computational complexity. FDR algorithms estimate a dense displacement field by interpolating a sp...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	160,667
1206.3633	Feature Based Fuzzy Rule Base Design for Image Extraction	In the recent advancement of multimedia technologies, it becomes a major concern of detecting visual attention regions in the field of image processing. The popularity of the terminal devices in a heterogeneous environment of the multimedia technology gives us enough scope for the betterment of image visualization. Alt...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	16,584
2308.06221	Automated Sizing and Training of Efficient Deep Autoencoders using Second Order Algorithms	We propose a multi-step training method for designing generalized linear classifiers. First, an initial multi-class linear classifier is found through regression. Then validation error is minimized by pruning of unnecessary inputs. Simultaneously, desired outputs are improved via a method similar to the Ho-Kashyap rule...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	385,066
2112.13846	Algorithm for recognizing the contour of a honeycomb block	The article discusses an algorithm for recognizing the contour of fragments of a honeycomb block. The inapplicability of ready-made functions of the OpenCV library is shown. Two proposed algorithms are considered. The direct scanning algorithm finds the extreme white pixels in the binarized image, it works adequately o...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	273,376
2404.05819	Just Wing It: Near-Optimal Estimation of Missing Mass in a Markovian Sequence	We study the problem of estimating the stationary mass -- also called the unigram mass -- that is missing from a single trajectory of a discrete-time, ergodic Markov chain. This problem has several applications -- for example, estimating the stationary missing mass is critical for accurately smoothing probability estim...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	445,219
2403.00632	Metamorpheus: Interactive, Affective, and Creative Dream Narration Through Metaphorical Visual Storytelling	Human emotions are essentially molded by lived experiences, from which we construct personalised meaning. The engagement in such meaning-making process has been practiced as an intervention in various psychotherapies to promote wellness. Nevertheless, to support recollecting and recounting lived experiences in everyday...	true	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	434,049
1305.4684	End-to-end interstellar communication system design for power efficiency	Radio communication over interstellar distances is studied, accounting for noise, dispersion, scattering and motion. Large transmitted powers suggest maximizing power efficiency (ratio of information rate to average signal power) as opposed to restricting bandwidth. The fundamental limit to reliable communication is de...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	24,709
2103.09179	Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection	Segmentation-based methods are widely used for scene text detection due to their superiority in describing arbitrary-shaped text instances. However, two major problems still exist: 1) current label generation techniques are mostly empirical and lack theoretical support, discouraging elaborate label design; 2) as a resu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	225,103
2204.04874	Augmentation-Free Graph Contrastive Learning with Performance Guarantee	Graph contrastive learning (GCL) is the most representative and prevalent self-supervised learning approach for graph-structured data. Despite its remarkable success, existing GCL methods highly rely on an augmentation scheme to learn the representations invariant across different augmentation views. In this work, we r...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	290,822
2211.09518	ImLiDAR: Cross-Sensor Dynamic Message Propagation Network for 3D Object Detection	LiDAR and camera, as two different sensors, supply geometric (point clouds) and semantic (RGB images) information of 3D scenes. However, it is still challenging for existing methods to fuse data from the two cross sensors, making them complementary for quality 3D object detection (3OD). We propose ImLiDAR, a new 3OD pa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,002
1808.07016	Gaussian Word Embedding with a Wasserstein Distance Loss	Compared with word embedding based on point representation, distribution-based word embedding shows more flexibility in expressing uncertainty and therefore embeds richer semantic information when representing words. The Wasserstein distance provides a natural notion of dissimilarity with probability measures and has a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	105,650
2405.04687	Towards Human-AI Mutual Learning: A New Research Paradigm	This paper describes a new research paradigm for studying human-AI collaboration, named "human-AI mutual learning", defined as the process where humans and AI agents preserve, exchange, and improve knowledge during human-AI collaboration. We describe relevant methodologies, motivations, domain examples, benefits, chall...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	452,641
2405.14759	Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training	In this paper, we investigate the challenging framework of Byzantine-robust training in distributed machine learning (ML) systems, focusing on enhancing both efficiency and practicality. As distributed ML systems become integral for complex ML tasks, ensuring resilience against Byzantine failures-where workers may cont...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	456,586
2502.03671	Advancing Reasoning in Large Language Models: Promising Methods and Approaches	Large Language Models (LLMs) have succeeded remarkably in various natural language processing (NLP) tasks, yet their reasoning capabilities remain a fundamental challenge. While LLMs exhibit impressive fluency and factual recall, their ability to perform complex reasoning-spanning logical deduction, mathematical proble...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	530,809
2004.01122	On the Principles of Differentiable Quantum Programming Languages	Variational Quantum Circuits (VQCs), or the so-called quantum neural-networks, are predicted to be one of the most important near-term quantum applications, not only because of their similar promises as classical neural-networks, but also because of their feasibility on near-term noisy intermediate-size quantum (NISQ) ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	170,820
2404.17269	Clustering of Motion Trajectories by a Distance Measure Based on Semantic Features	Clustering of motion trajectories is highly relevant for human-robot interactions as it allows the anticipation of human motions, fast reaction to those, as well as the recognition of explicit gestures. Further, it allows automated analysis of recorded motion data. Many clustering algorithms for trajectories build upon...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	449,801
2411.09007	Scale Contrastive Learning with Selective Attentions for Blind Image Quality Assessment	Blind image quality assessment (BIQA) serves as a fundamental task in computer vision, yet it often fails to consistently align with human subjective perception. Recent advances show that multi-scale evaluation strategies are promising due to their ability to replicate the hierarchical structure of human vision. Howeve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	508,099
2107.05583	Few-shot Learning with Global Relatedness Decoupled-Distillation	Despite the success that metric learning based approaches have achieved in few-shot learning, recent works reveal the ineffectiveness of their episodic training mode. In this paper, we point out two potential reasons for this problem: 1) the random episodic labels can only provide limited supervision information, while...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	245,826
2106.11486	Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification	We propose unsupervised embedding adaptation for the downstream few-shot classification task. Based on findings that deep neural networks learn to generalize before memorizing, we develop Early-Stage Feature Reconstruction (ESFR) -- a novel adaptation scheme with feature reconstruction and dimensionality-driven early s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	242,410
2110.01705	Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning	Explaining an image with missing or non-existent objects is known as object bias (hallucination) in image captioning. This behaviour is quite common in the state-of-the-art captioning models which is not desirable by humans. To decrease the object hallucination in captioning, we propose three simple yet efficient train...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	258,856
2406.08997	Adaptive Temporal Motion Guided Graph Convolution Network for Micro-expression Recognition	Micro-expressions serve as essential cues for understanding individuals' genuine emotional states. Recognizing micro-expressions attracts increasing research attention due to its various applications in fields such as business negotiation and psychotherapy. However, the intricate and transient nature of micro-expressio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	463,718
2212.11125	A new weighted ensemble model for phishing detection based on feature selection	A phishing attack is a sort of cyber assault in which the attacker sends fake communications to entice a human victim to provide personal information or credentials. Phishing website identification can assist visitors in avoiding becoming victims of these assaults. The phishing problem is increasing day by day, and the...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	337,703
1601.00416	Computing Robust Controlled Invariant Sets of Linear Systems	We consider controllable linear discrete-time systems with bounded perturbations and present two methods to compute robust controlled invariant sets. The first method tolerates an arbitrarily small constraint violation to compute an arbitrarily precise outer approximation of the maximal robust controlled invariant set,...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	50,646
2011.04216	DoWhy: An End-to-End Library for Causal Inference	In addition to efficient statistical estimators of a treatment's effect, successful application of causal inference requires specifying assumptions about the mechanisms underlying observed data and testing whether they are valid, and to what extent. However, most libraries for causal inference focus only on the task of...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	205,506
1912.05372	FlauBERT: Unsupervised Language Model Pre-training for French	Language models have become a key step to achieve state-of-the art results in many different Natural Language Processing (NLP) tasks. Leveraging the huge amount of unlabeled texts nowadays available, they provide an efficient way to pre-train continuous word representations that can be fine-tuned for a downstream task,...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	157,091
2309.15462	DTC: Deep Tracking Control	Legged locomotion is a complex control problem that requires both accuracy and robustness to cope with real-world challenges. Legged systems have traditionally been controlled using trajectory optimization with inverse dynamics. Such hierarchical model-based methods are appealing due to intuitive cost function tuning, ...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	394,974
2403.06835	Medical Image Synthesis via Fine-Grained Image-Text Alignment and Anatomy-Pathology Prompting	Data scarcity and privacy concerns limit the availability of high-quality medical images for public use, which can be mitigated through medical image synthesis. However, current medical image synthesis methods often struggle to accurately capture the complexity of detailed anatomical structures and pathological conditi...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	436,626
2401.07810	Consolidating Strategies for Countering Hate Speech Using Persuasive Dialogues	Hateful comments are prevalent on social media platforms. Although tools for automatically detecting, flagging, and blocking such false, offensive, and harmful content online have lately matured, such reactive and brute force methods alone provide short-term and superficial remedies while the perpetrators persist. With...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	421,665
2304.04600	Rotation-Scale Equivariant Steerable Filters	Incorporating either rotation equivariance or scale equivariance into CNNs has proved to be effective in improving models' generalization performance. However, jointly integrating rotation and scale equivariance into CNNs has not been widely explored. Digital histology imaging of biopsy tissue can be captured at arbitr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,281
2203.15109	27 Open Problems in Kolmogorov Complexity	The paper proposes open problems in classical Kolmogorov complexity. Each problem is presented with background information and thus the article also surveys some recent studies in the area.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	288,240
2403.16967	Visual Whole-Body Control for Legged Loco-Manipulation	We study the problem of mobile manipulation using legged robots equipped with an arm, namely legged loco-manipulation. The robot legs, while usually utilized for mobility, offer an opportunity to amplify the manipulation capabilities by conducting whole-body control. That is, the robot can control the legs and the arm ...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	441,260
2309.02623	Superclustering by finding statistically significant separable groups of optimal gaussian clusters	The paper presents the algorithm for clustering a dataset by grouping the optimal, from the point of view of the BIC criterion, number of Gaussian clusters into the optimal, from the point of view of their statistical separability, superclusters. The algorithm consists of three stages: representation of the dataset a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	390,107
1911.10686	Zero-Shot Imitating Collaborative Manipulation Plans from YouTube Cooking Videos	People often watch videos on the web to learn how to cook new recipes, assemble furniture or repair a computer. We wish to enable robots with the very same capability. This is challenging; there is a large variation in manipulation actions and some videos even involve multiple persons, who collaborate by sharing and ex...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	154,909
1712.00269	GANosaic: Mosaic Creation with Generative Texture Manifolds	This paper presents a novel framework for generating texture mosaics with convolutional neural networks. Our method is called GANosaic and performs optimization in the latent noise space of a generative texture model, which allows the transformation of a content image into a mosaic exhibiting the visual properties of t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,870
2212.09010	Risk-Sensitive Reinforcement Learning with Exponential Criteria	While reinforcement learning has shown experimental success in a number of applications, it is known to be sensitive to noise and perturbations in the parameters of the system, leading to high variance in the total reward amongst different episodes in slightly different environments. To introduce robustness, as well as...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	336,961
2501.05852	MRI Patterns of the Hippocampus and Amygdala for Predicting Stages of Alzheimer's Progression: A Minimal Feature Machine Learning Framework	Alzheimer's disease (AD) progresses through distinct stages, from early mild cognitive impairment (EMCI) to late mild cognitive impairment (LMCI) and eventually to AD. Accurate identification of these stages, especially distinguishing LMCI from EMCI, is crucial for developing pre-dementia treatments but remains challen...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	523,748
1904.12617	Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes	PURPOSE: The medical literature relevant to germline genetics is growing exponentially. Clinicians need tools monitoring and prioritizing the literature to understand the clinical implications of the pathogenic genetic variants. We developed and evaluated two machine learning models to classify abstracts as relevant to...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	129,163
2105.07122	Premise-based Multimodal Reasoning: Conditional Inference on Joint Textual and Visual Clues	It is a common practice for recent works in vision language cross-modal reasoning to adopt a binary or multi-choice classification formulation taking as input a set of source image(s) and textual query. In this work, we take a sober look at such an unconditional formulation in the sense that no prior knowledge is speci...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	235,324
2007.02934	The Effects of Taxes on Wealth Inequality in Artificial Chemistry Models of Economic Activity	We consider a number of Artificial Chemistry models for economic activity and what consequences they have for the formation of economic inequality. We are particularly interested in what tax measures are effective in dampening economic inequality. By starting from well-known kinetic exchange models, we examine differen...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	185,908
2209.09008	Encrypted Semantic Communication Using Adversarial Training for Privacy Preserving	Semantic communication is implemented based on shared background knowledge, but the sharing mechanism risks privacy leakage. In this letter, we propose an encrypted semantic communication system (ESCS) for privacy preserving, which combines universality and confidentiality. The universality is reflected in that all net...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	318,343
2109.01368	The full Low-carbon Expansion Generation Optimization (LEGO) model	This paper introduces the full Low-carbon Expansion Generation Optimization (LEGO) model available on Github (https://github.com/wogrin/LEGO). LEGO is a mixed-integer quadratically constrained optimization problem and has been designed to be a multi-purpose tool, like a Swiss army knife, that can be employed to study m...	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	253,416
1508.04924	Distributed Compressive Sensing: A Deep Learning Approach	Various studies that address the compressed sensing problem with Multiple Measurement Vectors (MMVs) have been recently carried. These studies assume the vectors of the different channels to be jointly sparse. In this paper, we relax this condition. Instead we assume that these sparse vectors depend on each other but t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	46,181
2411.05107	MissionGPT: Mission Planner for Mobile Robot based on Robotics Transformer Model	This paper presents a novel approach to building mission planners based on neural networks with Transformer architecture and Large Language Models (LLMs). This approach demonstrates the possibility of setting a task for a mobile robot and its successful execution without the use of perception algorithms, based only on ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	506,550
1609.08408	Deep learning for detection of bird vocalisations	This work focuses on reliable detection of bird sound emissions as recorded in the open field. Acoustic detection of avian sounds can be used for the automatized monitoring of multiple bird taxa and querying in long-term recordings for species of interest for researchers, conservation practitioners, and decision makers...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	61,584
0807.2475	Opportunistic Collaborative Beamforming with One-Bit Feedback	An energy-efficient opportunistic collaborative beamformer with one-bit feedback is proposed for ad hoc sensor networks over Rayleigh fading channels. In contrast to conventional collaborative beamforming schemes in which each source node uses channel state information to correct its local carrier offset and channel ph...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,068
cs/9402102	Substructure Discovery Using Minimum Description Length and Background Knowledge	The ability to identify interesting and repetitive substructures is an essential component to discovering knowledge in structural data. We describe a new version of our SUBDUE substructure discovery system based on the minimum description length principle. The SUBDUE system discovers substructures that compress the ori...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	540,288
2111.14988	Adversarial Training for a Hybrid Approach to Aspect-Based Sentiment Analysis	The increasing popularity of the Web has subsequently increased the abundance of reviews on products and services. Mining these reviews for expressed sentiment is beneficial for both companies and consumers, as quality can be improved based on this information. In this paper, we consider the state-of-the-art HAABSA++ a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	268,765
2108.12752	TAR on Social Media: A Framework for Online Content Moderation	Content moderation (removing or limiting the distribution of posts based on their contents) is one tool social networks use to fight problems such as harassment and disinformation. Manually screening all content is usually impractical given the scale of social media data, and the need for nuanced human interpretations ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	252,599
2207.00865	ORA3D: Overlap Region Aware Multi-view 3D Object Detection	Current multi-view 3D object detection methods often fail to detect objects in the overlap region properly, and the networks' understanding of the scene is often limited to that of a monocular detection network. Moreover, objects in the overlap region are often largely occluded or suffer from deformation due to camera ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	305,936
2501.01679	Adaptive Few-shot Prompting for Machine Translation with Pre-trained Language Models	Recently, Large language models (LLMs) with in-context learning have demonstrated remarkable potential in handling neural machine translation. However, existing evidence shows that LLMs are prompt-sensitive and it is sub-optimal to apply the fixed prompt to any input for downstream machine translation tasks. To address...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	522,162
2104.11184	A continuous fracture front tracking algorithm with multi layer tip elements (MuLTipEl) for a plane strain hydraulic fracture	The problem of a plane strain hydraulic fracture propagating in a layered formation is considered. Fracture toughness, in-situ stress, and leak-off coefficient are assumed to vary by layer, while the elastic properties are kept constant throughout the domain for simplicity. The purpose of this study is to develop a num...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	231,846
2402.08282	Logic of Awareness for Nested Knowledge	Reasoning abilities of human beings are limited. Logics that treat logical inference for human knowledge should reflect these limited abilities. Logic of awareness is one of those logics. In the logic, what an agent with a limited reasoning ability actually knows at a given moment (explicit knowledge) is distinguished ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	429,045
2311.12282	Orthogonally weighted $\ell_{2,1}$ regularization for rank-aware joint sparse recovery: algorithm and analysis	We propose and analyze an efficient algorithm for solving the joint sparse recovery problem using a new regularization-based method, named orthogonally weighted $\ell_{2,1}$ ($\mathit{ow}\ell_{2,1}$), which is specifically designed to take into account the rank of the solution matrix. This method has applications in fe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	409,271
1809.05000	From Nonlinear Identification to Linear Parameter Varying Models: Benchmark Examples	Linear parameter-varying (LPV) models form a powerful model class to analyze and control a (nonlinear) system of interest. Identifying a LPV model of a nonlinear system can be challenging due to the difficulty of selecting the scheduling variable(s) a priori, which is quite challenging in case a first principles based ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	107,697
2002.12478	Time Series Data Augmentation for Deep Learning: A Survey	Deep learning performs remarkably well on many time series analysis tasks recently. The superior performance of deep neural networks relies heavily on a large number of training data to avoid overfitting. However, the labeled data of many real-world time series applications may be limited such as classification in medi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	166,046

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