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
1708.01155	Deep MR to CT Synthesis using Unpaired Data	MR-only radiotherapy treatment planning requires accurate MR-to-CT synthesis. Current deep learning methods for MR-to-CT synthesis depend on pairwise aligned MR and CT training images of the same patient. However, misalignment between paired images could lead to errors in synthesized CT images. To overcome this, we pro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,342
2005.07109	The $\alpha$-$\eta$-$\mathcal{F}$ and $\alpha$-$\kappa$-$\mathcal{F}$ Composite Fading Distributions	In this paper, we present the $\alpha$-$\eta$-$\mathcal{F}$ and $\alpha$-$\kappa$-$\mathcal{F}$ composite fading distributions. The two distributions generalize the two well-known composite fading distributions, namely the $\eta$-$\mu$/inverse gamma and the $\kappa$-$\mu$/inverse gamma distributions. For both distribut...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	177,195
2108.03554	Semantic-Based Explainable AI: Leveraging Semantic Scene Graphs and Pairwise Ranking to Explain Robot Failures	When interacting in unstructured human environments, occasional robot failures are inevitable. When such failures occur, everyday people, rather than trained technicians, will be the first to respond. Existing natural language explanations hand-annotate contextual information from an environment to help everyday people...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	249,699
2310.14228	Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection	Unsupervised image Anomaly Detection (UAD) aims to learn robust and discriminative representations of normal samples. While separate solutions per class endow expensive computation and limited generalizability, this paper focuses on building a unified framework for multiple classes. Under such a challenging setting, po...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	401,772
2204.02371	Optical Proximity Sensing for Pose Estimation During In-Hand Manipulation	During in-hand manipulation, robots must be able to continuously estimate the pose of the object in order to generate appropriate control actions. The performance of algorithms for pose estimation hinges on the robot's sensors being able to detect discriminative geometric object features, but previous sensing modalitie...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	289,918
2407.14114	A3Rank: Augmentation Alignment Analysis for Prioritizing Overconfident Failing Samples for Deep Learning Models	Sharpening deep learning models by training them with examples close to the decision boundary is a well-known best practice. Nonetheless, these models are still error-prone in producing predictions. In practice, the inference of the deep learning models in many application systems is guarded by a rejector, such as a co...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	474,656
2112.08073	Analysis of Leading Communities Contributing to arXiv Information Distribution on Twitter	To analyze the impact that arXiv is having on the world, in this paper we propose an arXiv information distribution model on Twitter, which has a three-layer structure: arXiv papers, information spreaders, and information collectors. First, we use the HITS algorithm to analyze the arXiv information diffusion network wi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	271,686
2403.05005	DITTO: Dual and Integrated Latent Topologies for Implicit 3D Reconstruction	We propose a novel concept of dual and integrated latent topologies (DITTO in short) for implicit 3D reconstruction from noisy and sparse point clouds. Most existing methods predominantly focus on single latent type, such as point or grid latents. In contrast, the proposed DITTO leverages both point and grid latents (i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	435,821
2411.00969	Magnitude Pruning of Large Pretrained Transformer Models with a Mixture Gaussian Prior	Large pretrained transformer models have revolutionized modern AI applications with their state-of-the-art performance in natural language processing (NLP). However, their substantial parameter count poses challenges for real-world deployment. To address this, researchers often reduce model size by pruning parameters b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,853
1705.02148	Unified Embedding and Metric Learning for Zero-Exemplar Event Detection	Event detection in unconstrained videos is conceived as a content-based video retrieval with two modalities: textual and visual. Given a text describing a novel event, the goal is to rank related videos accordingly. This task is zero-exemplar, no video examples are given to the novel event. Related works train a bank...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	72,940
1705.03524	Multi-Scale Spatially Weighted Local Histograms in O(1)	Weighting pixel contribution considering its location is a key feature in many fundamental image processing tasks including filtering, object modeling and distance matching. Several techniques have been proposed that incorporate Spatial information to increase the accuracy and boost the performance of detection, tracki...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,198
1905.00609	Synthetic Oversampling of Multi-Label Data based on Local Label Distribution	Class-imbalance is an inherent characteristic of multi-label data which affects the prediction accuracy of most multi-label learning methods. One efficient strategy to deal with this problem is to employ resampling techniques before training the classifier. Existing multilabel sampling methods alleviate the (global) im...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	129,523
1502.01139	Generalized modularity matrices	Various modularity matrices appeared in the recent literature on network analysis and algebraic graph theory. Their purpose is to allow writing as quadratic forms certain combinatorial functions appearing in the framework of graph clustering problems. In this paper we put in evidence certain common traits of various mo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	39,906
2106.02234	Discovery of Causal Additive Models in the Presence of Unobserved Variables	Causal discovery from data affected by unobserved variables is an important but difficult problem to solve. The effects that unobserved variables have on the relationships between observed variables are more complex in nonlinear cases than in linear cases. In this study, we focus on causal additive models in the presen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	238,782
2305.02449	Bayesian Safety Validation for Failure Probability Estimation of Black-Box Systems	Estimating the probability of failure is an important step in the certification of safety-critical systems. Efficient estimation methods are often needed due to the challenges posed by high-dimensional input spaces, risky test scenarios, and computationally expensive simulators. This work frames the problem of black-bo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	362,034
2307.16714	A Comprehensive Study of Machine Learning Techniques for Log-Based Anomaly Detection	Growth in system complexity increases the need for automated log analysis techniques, such as Log-based Anomaly Detection (LAD). While deep learning (DL) methods have been widely used for LAD, traditional machine learning (ML) techniques can also perform well depending on the context and dataset. Semi-supervised techni...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	382,711
1410.0547	Design Mining Interacting Wind Turbines	An initial study of surrogate-assisted evolutionary algorithms used to design vertical-axis wind turbines wherein candidate prototypes are evaluated under fan generated wind conditions after being physically instantiated by a 3D printer has recently been presented. Unlike other approaches, such as computational fluid d...	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	36,479
2011.09039	Sequence-Level Mixed Sample Data Augmentation	Despite their empirical success, neural networks still have difficulty capturing compositional aspects of natural language. This work proposes a simple data augmentation approach to encourage compositional behavior in neural models for sequence-to-sequence problems. Our approach, SeqMix, creates new synthetic examples ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	207,070
2104.03224	Efficient and Accurate In-Database Machine Learning with SQL Code Generation in Python	Following an analysis of the advantages of SQL-based Machine Learning (ML) and a short literature survey of the field, we describe a novel method for In-Database Machine Learning (IDBML). We contribute a process for SQL-code generation in Python using template macros in Jinja2 as well as the prototype implementation of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	229,014
2302.12161	Distributed State Estimation for Jointly Observable Linear Systems over Time-varying Networks	This paper deals with a distributed state estimation problem for jointly observable multi-agent systems operated over various time-varying network topologies. The results apply when the system matrix of the system to be observed contains eigenvalues with positive real parts. They also can apply to situations where the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	347,456
2407.11686	CCoE: A Compact and Efficient LLM Framework with Multi-Expert Collaboration for Resource-Limited Settings	Large Language Models (LLMs) have achieved exceptional performance across diverse domains through training on massive datasets. However, scaling LLMs to support multiple downstream domain applications remains a significant challenge, especially under resource constraints. Existing approaches often struggle to balance p...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	473,574
2409.08974	Thermal Modelling of Battery Cells for Optimal Tab and Surface Cooling Control	Optimal cooling that minimises thermal gradients and the average temperature is essential for enhanced battery safety and health. This work presents a new modelling approach for battery cells of different shapes by integrating Chebyshev spectral-Galerkin method and model component decomposition. As a result, a library ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	488,124
2207.05477	HelixFold: An Efficient Implementation of AlphaFold2 using PaddlePaddle	Accurate protein structure prediction can significantly accelerate the development of life science. The accuracy of AlphaFold2, a frontier end-to-end structure prediction system, is already close to that of the experimental determination techniques. Due to the complex model architecture and large memory consumption, it...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	307,555
2409.10202	SteeredMarigold: Steering Diffusion Towards Depth Completion of Largely Incomplete Depth Maps	Even if the depth maps captured by RGB-D sensors deployed in real environments are often characterized by large areas missing valid depth measurements, the vast majority of depth completion methods still assumes depth values covering all areas of the scene. To address this limitation, we introduce SteeredMarigold, a tr...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	488,659
2209.10778	Nesting Forward Automatic Differentiation for Memory-Efficient Deep Neural Network Training	An activation function is an element-wise mathematical function and plays a crucial role in deep neural networks (DNN). Many novel and sophisticated activation functions have been proposed to improve the DNN accuracy but also consume massive memory in the training process with back-propagation. In this study, we propos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	318,964
2009.00418	Machine Reasoning Explainability	As a field of AI, Machine Reasoning (MR) uses largely symbolic means to formalize and emulate abstract reasoning. Studies in early MR have notably started inquiries into Explainable AI (XAI) -- arguably one of the biggest concerns today for the AI community. Work on explainable MR as well as on MR approaches to explain...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	194,042
2409.07763	Reimagining Linear Probing: Kolmogorov-Arnold Networks in Transfer Learning	This paper introduces Kolmogorov-Arnold Networks (KAN) as an enhancement to the traditional linear probing method in transfer learning. Linear probing, often applied to the final layer of pre-trained models, is limited by its inability to model complex relationships in data. To address this, we propose substituting the...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	487,650
2205.14318	Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions	Pretrained language models have shown superior performance on many natural language processing tasks, yet they still struggle at multi-step formal reasoning tasks like grade school math problems. One key challenge of finetuning them to solve such math reasoning problems is that many existing datasets only contain one r...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	299,309
1601.06676	Plausible Deniability over Broadcast Channels	In this paper, we introduce the notion of Plausible Deniability in an information theoretic framework. We consider a scenario where an entity that eavesdrops through a broadcast channel summons one of the parties in a communication protocol to reveal their message (or signal vector). It is desirable that the summoned p...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	51,318
1411.6792	Conditional probability calculations for the nonlinear Schr\"odinger equation with additive noise	The method for computation of conditional probability density function for the nonlinear Schr\"odinger equation with additive noise is developed. We present in a constructive form the conditional probability density function in the limit of a small noise and analytically derive it in a weakly nonlinear case. The genera...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	37,874
2312.09517	A wearable Gait Assessment Method for Lumbar Disc Herniation Based on Adaptive Kalman Filtering	Lumbar disc herniation (LDH) is a prevalent orthopedic condition in clinical practice. Inertial measurement unit sensors (IMUs) are an effective tool for monitoring and assessing gait impairment in patients with lumbar disc herniation (LDH). However, the current gait assessment of LDH focuses solely on single-source ac...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	415,762
2402.18617	ELA: Exploited Level Augmentation for Offline Learning in Zero-Sum Games	Offline learning has become widely used due to its ability to derive effective policies from offline datasets gathered by expert demonstrators without interacting with the environment directly. Recent research has explored various ways to enhance offline learning efficiency by considering the characteristics (e.g., exp...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	true	433,501
2105.07132	Offline Time-Independent Multi-Agent Path Planning	This paper studies a novel planning problem for multiple agents that cannot share holding resources, named OTIMAPP (Offline Time-Independent Multi-Agent Path Planning). Given a graph and a set of start-goal pairs, the problem consists in assigning a path to each agent such that every agent eventually reaches their goal...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	235,328
1910.11306	Controllable Attention for Structured Layered Video Decomposition	The objective of this paper is to be able to separate a video into its natural layers, and to control which of the separated layers to attend to. For example, to be able to separate reflections, transparency or object motion. We make the following three contributions: (i) we introduce a new structured neural network ar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	150,740
2003.08042	STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition	Effective and Efficient spatio-temporal modeling is essential for action recognition. Existing methods suffer from the trade-off between model performance and model complexity. In this paper, we present a novel Spatio-Temporal Hybrid Convolution Network (denoted as "STH") which simultaneously encodes spatial and tempor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,620
2305.08573	A graph convolutional autoencoder approach to model order reduction for parametrized PDEs	The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real-time and many-query evaluations of parametric Partial Differential Equations (PDEs). Linear techniques such as ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	364,332
2302.10315	Generalization algorithm of multimodal pre-training model based on graph-text self-supervised training	Recently, a large number of studies have shown that the introduction of visual information can effectively improve the effect of neural machine translation (NMT). Its effectiveness largely depends on the availability of a large number of bilingual parallel sentence pairs and manual image annotation. The lack of images ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	346,758
1710.00398	Wikipedia graph mining: dynamic structure of collective memory	Wikipedia is the biggest encyclopedia ever created and the fifth most visited website in the world. Tens of millions of people surf it every day, seeking answers to various questions. Collective user activity on its pages leaves publicly available footprints of human behavior, making Wikipedia an excellent source for a...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	81,855
1906.04474	Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis	Considering a two-user multi-antenna Broadcast Channel, this paper shows that linearly precoded Rate-Splitting (RS) with Successive Interference Cancellation (SIC) receivers is a flexible framework for non-orthogonal transmission that generalizes, and subsumes as special cases, four seemingly different strategies, name...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	134,730
1504.07857	Probabilistic Depth Image Registration incorporating Nonvisual Information	In this paper, we derive a probabilistic registration algorithm for object modeling and tracking. In many robotics applications, such as manipulation tasks, nonvisual information about the movement of the object is available, which we will combine with the visual information. Furthermore we do not only consider observa...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	42,581
2205.12262	PINO-MBD: Physics-informed Neural Operator for Solving Coupled ODEs in Multi-body Dynamics	In multi-body dynamics, the motion of a complicated physical object is described as a coupled ordinary differential equation system with multiple unknown solutions. Engineers need to constantly adjust the object to meet requirements at the design stage, where a highly efficient solver is needed. The rise of machine lea...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	298,470
2205.14552	Staggered Rollout Designs Enable Causal Inference Under Interference Without Network Knowledge	Randomized experiments are widely used to estimate causal effects across a variety of domains. However, classical causal inference approaches rely on critical independence assumptions that are violated by network interference, when the treatment of one individual influences the outcomes of others. All existing approach...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	299,404
2005.12214	Passivity-based distributed acquisition and station-keeping control of a satellite constellation in areostationary orbit	We present a distributed control law to assemble a cluster of satellites into an equally-spaced, planar constellation in a desired circular orbit about a planet. We assume each satellite only uses local information, transmitted through communication links with neighboring satellites. The same control law is used to mai...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	178,674
2311.18705	Quantifying metadata relevance to network block structure using description length	Network analysis is often enriched by including an examination of node metadata. In the context of understanding the mesoscale of networks it is often assumed that node groups based on metadata and node groups based on connectivity patterns are intrinsically linked. This assumption is increasingly being challenged, whe...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	411,781
2111.00341	Causal Discovery in Linear Structural Causal Models with Deterministic Relations	Linear structural causal models (SCMs) -- in which each observed variable is generated by a subset of the other observed variables as well as a subset of the exogenous sources -- are pervasive in causal inference and casual discovery. However, for the task of causal discovery, existing work almost exclusively focus on ...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	264,186
1511.04136	UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking	In recent years, numerous effective multi-object tracking (MOT) methods are developed because of the wide range of applications. Existing performance evaluations of MOT methods usually separate the object tracking step from the object detection step by using the same fixed object detection results for comparisons. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,848
2408.05631	PRTGaussian: Efficient Relighting Using 3D Gaussians with Precomputed Radiance Transfer	We present PRTGaussian, a realtime relightable novel-view synthesis method made possible by combining 3D Gaussians and Precomputed Radiance Transfer (PRT). By fitting relightable Gaussians to multi-view OLAT data, our method enables real-time, free-viewpoint relighting. By estimating the radiance transfer based on high...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	479,869
1904.05168	Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning	Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental time. We present a proof-of-concept of application of deep learning and neural network for high-quality, reliable, and very fast NMR spectra reconstruction from limited experim...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	127,230
2309.02669	Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning	We study the budget allocation problem in online marketing campaigns that utilize previously collected offline data. We first discuss the long-term effect of optimizing marketing budget allocation decisions in the offline setting. To overcome the challenge, we propose a novel game-theoretic offline value-based reinforc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	390,122
1909.05855	Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset	Virtual assistants such as Google Assistant, Alexa and Siri provide a conversational interface to a large number of services and APIs spanning multiple domains. Such systems need to support an ever-increasing number of services with possibly overlapping functionality. Furthermore, some of these services have little to ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	145,227
2412.01935	Cross Domain Adaptation using Adversarial networks with Cyclic loss	Deep Learning methods are highly local and sensitive to the domain of data they are trained with. Even a slight deviation from the domain distribution affects prediction accuracy of deep networks significantly. In this work, we have investigated a set of techniques aimed at increasing accuracy of generator networks whi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	513,311
2106.01786	What Happened Next? Using Deep Learning to Value Defensive Actions in Football Event-Data	Objectively quantifying the value of player actions in football (soccer) is a challenging problem. To date, studies in football analytics have mainly focused on the attacking side of the game, while there has been less work on event-driven metrics for valuing defensive actions (e.g., tackles and interceptions). Therefo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	238,625
2202.09050	Guide Local Feature Matching by Overlap Estimation	Local image feature matching under large appearance, viewpoint, and distance changes is challenging yet important. Conventional methods detect and match tentative local features across the whole images, with heuristic consistency checks to guarantee reliable matches. In this paper, we introduce a novel Overlap Estimati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	281,080
1011.4833	A Logical Charaterisation of Ordered Disjunction	In this paper we consider a logical treatment for the ordered disjunction operator 'x' introduced by Brewka, Niemel\"a and Syrj\"anen in their Logic Programs with Ordered Disjunctions (LPOD). LPODs are used to represent preferences in logic programming under the answer set semantics. Their semantics is defined by first...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	8,301
2307.11542	Extreme Level Crossing Rate: A New Performance Indicator for URLLC Systems	Level crossing rate (LCR) is a well-known statistical tool that is related to the duration of a random stationary fading process \emph{on average}. In doing so, LCR cannot capture the behavior of \emph{extremely rare} random events. Nonetheless, the latter events play a key role in the performance of ultra-reliable and...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	380,946
1401.0395	Hybrid Approach to Face Recognition System using Principle component and Independent component with score based fusion process	Hybrid approach has a special status among Face Recognition Systems as they combine different recognition approaches in an either serial or parallel to overcome the shortcomings of individual methods. This paper explores the area of Hybrid Face Recognition using score based strategy as a combiner/fusion process. In pro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	29,553
2311.06454	A Saliency-based Clustering Framework for Identifying Aberrant Predictions	In machine learning, classification tasks serve as the cornerstone of a wide range of real-world applications. Reliable, trustworthy classification is particularly intricate in biomedical settings, where the ground truth is often inherently uncertain and relies on high degrees of human expertise for labeling. Tradition...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	406,946
2112.03178	Student of Games: A unified learning algorithm for both perfect and imperfect information games	Games have a long history as benchmarks for progress in artificial intelligence. Approaches using search and learning produced strong performance across many perfect information games, and approaches using game-theoretic reasoning and learning demonstrated strong performance for specific imperfect information poker var...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	270,109
1802.01880	Learning Image Representations by Completing Damaged Jigsaw Puzzles	In this paper, we explore methods of complicating self-supervised tasks for representation learning. That is, we do severe damage to data and encourage a network to recover them. First, we complicate each of three powerful self-supervised task candidates: jigsaw puzzle, inpainting, and colorization. In addition, we int...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,680
1910.04851	Addressing Failure Prediction by Learning Model Confidence	Assessing reliably the confidence of a deep neural network and predicting its failures is of primary importance for the practical deployment of these models. In this paper, we propose a new target criterion for model confidence, corresponding to the True Class Probability (TCP). We show how using the TCP is more suited...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	148,873
0901.2483	Fast Encoding and Decoding of Gabidulin Codes	Gabidulin codes are the rank-metric analogs of Reed-Solomon codes and have a major role in practical error control for network coding. This paper presents new encoding and decoding algorithms for Gabidulin codes based on low-complexity normal bases. In addition, a new decoding algorithm is proposed based on a transform...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,991
2402.16288	PerLTQA: A Personal Long-Term Memory Dataset for Memory Classification, Retrieval, and Synthesis in Question Answering	Long-term memory plays a critical role in personal interaction, considering long-term memory can better leverage world knowledge, historical information, and preferences in dialogues. Our research introduces PerLTQA, an innovative QA dataset that combines semantic and episodic memories, including world knowledge, profi...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	432,496
2204.13004	Defending Person Detection Against Adversarial Patch Attack by using Universal Defensive Frame	Person detection has attracted great attention in the computer vision area and is an imperative element in human-centric computer vision. Although the predictive performances of person detection networks have been improved dramatically, they are vulnerable to adversarial patch attacks. Changing the pixels in a restrict...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,679
1910.00618	Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video	Pushing is a fundamental robotic skill. Existing work has shown how to exploit models of pushing to achieve a variety of tasks, including grasping under uncertainty, in-hand manipulation and clearing clutter. Such models, however, are approximate, which limits their applicability. Learning-based methods can reason dire...	false	false	false	false	false	false	true	true	false	false	true	true	false	false	false	false	false	false	147,712
2108.10510	Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking	Context information in search sessions has proven to be useful for capturing user search intent. Existing studies explored user behavior sequences in sessions in different ways to enhance query suggestion or document ranking. However, a user behavior sequence has often been viewed as a definite and exact signal reflect...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	251,914
2410.12835	A Dutch Financial Large Language Model	This paper presents FinGEITje, the first Dutch financial Large Language Model (LLM) specifically designed and optimized for various financial tasks. Together with the model, we release a specialized Dutch financial instruction tuning dataset with over 140,000 samples, constructed employing an automated translation and ...	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	499,224
2212.11851	StoRM: A Diffusion-based Stochastic Regeneration Model for Speech Enhancement and Dereverberation	Diffusion models have shown a great ability at bridging the performance gap between predictive and generative approaches for speech enhancement. We have shown that they may even outperform their predictive counterparts for non-additive corruption types or when they are evaluated on mismatched conditions. However, diffu...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	337,905
2311.08338	Self-Contained Calibration of an Elastic Humanoid Upper Body Using Only a Head-Mounted RGB Camera	When a humanoid robot performs a manipulation task, it first makes a model of the world using its visual sensors and then plans the motion of its body in this model. For this, precise calibration of the camera parameters and the kinematic tree is needed. Besides the accuracy of the calibrated model, the calibration pro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	407,681
2206.13127	Intelligent Omni-Surfaces (IOSs) for the MIMO Broadcast Channel	In this paper, we consider intelligent omni-surfaces (IOSs), which are capable of simultaneously reflecting and refracting electromagnetic waves. We focus our attention on the multiple-input multiple-output (MIMO) broadcast channel, and we introduce an algorithm for jointly optimizing the covariance matrix at the base ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	304,851
2311.17136	UniIR: Training and Benchmarking Universal Multimodal Information Retrievers	Existing information retrieval (IR) models often assume a homogeneous format, limiting their applicability to diverse user needs, such as searching for images with text descriptions, searching for a news article with a headline image, or finding a similar photo with a query image. To approach such different information...	false	false	false	false	true	true	false	false	true	false	false	true	false	false	false	false	false	false	411,193
1712.09684	Geometry Processing of Conventionally Produced Mouse Brain Slice Images	Brain mapping research in most neuroanatomical laboratories relies on conventional processing techniques, which often introduce histological artifacts such as tissue tears and tissue loss. In this paper we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mous...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	87,389
1804.04217	Stability of Leaderless Resource Consumption Networks	In this paper, we study the global stability properties of a multi-agent model of natural resource consumption that balances ecological and social network components in determining the consumption behavior of a group of agents. The social network is assumed to be leaderless, a condition that ensures that no single node...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	94,786
2203.09494	Transframer: Arbitrary Frame Prediction with Generative Models	We present a general-purpose framework for image modelling and vision tasks based on probabilistic frame prediction. Our approach unifies a broad range of tasks, from image segmentation, to novel view synthesis and video interpolation. We pair this framework with an architecture we term Transframer, which uses U-Net an...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	286,175
1811.05437	Argumentation for Explainable Scheduling (Full Paper with Proofs)	Mathematical optimization offers highly-effective tools for finding solutions for problems with well-defined goals, notably scheduling. However, optimization solvers are often unexplainable black boxes whose solutions are inaccessible to users and which users cannot interact with. We define a novel paradigm using argum...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	113,318
2202.01332	Training a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection	The network intrusion detection task is challenging because of the imbalanced and unlabeled nature of the dataset it operates on. Existing generative adversarial networks (GANs), are primarily used for creating synthetic samples from reals. They also have been proved successful in anomaly detection tasks. In our propos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,447
2102.04282	Communication-efficient k-Means for Edge-based Machine Learning	We consider the problem of computing the k-means centers for a large high-dimensional dataset in the context of edge-based machine learning, where data sources offload machine learning computation to nearby edge servers. k-Means computation is fundamental to many data analytics, and the capability of computing provably...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,058
1709.05374	General Phase Regularized Reconstruction using Phase Cycling	Purpose: To develop a general phase regularized image reconstruction method, with applications to partial Fourier imaging, water-fat imaging and flow imaging. Theory and Methods: The problem of enforcing phase constraints in reconstruction was studied under a regularized inverse problem framework. A general phase reg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	80,846
2102.01889	Multi-Instance Learning by Utilizing Structural Relationship among Instances	Multi-Instance Learning(MIL) aims to learn the mapping between a bag of instances and the bag-level label. Therefore, the relationships among instances are very important for learning the mapping. In this paper, we propose an MIL algorithm based on a graph built by structural relationship among instances within a bag. ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	218,252
1402.4360	An Elementary Completeness Proof for Secure Two-Party Computation Primitives	In the secure two-party computation problem, two parties wish to compute a (possibly randomized) function of their inputs via an interactive protocol, while ensuring that neither party learns more than what can be inferred from only their own input and output. For semi-honest parties and information-theoretic security ...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	30,956
2202.11345	Prompt-Learning for Short Text Classification	In the short text, the extremely short length, feature sparsity, and high ambiguity pose huge challenges to classification tasks. Recently, as an effective method for tuning Pre-trained Language Models for specific downstream tasks, prompt-learning has attracted a vast amount of attention and research. The main intuiti...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	281,859
2111.00086	Measuring a Texts Fairness Dimensions Using Machine Learning Based on Social Psychological Factors	Fairness is a principal social value that can be observed in civilisations around the world. A manifestation of this is in social agreements, often described in texts, such as contracts. Yet, despite the prevalence of such, a fairness metric for texts describing a social act remains wanting. To address this, we take a ...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	264,091
2401.12076	Human Impression of Humanoid Robots Mirroring Social Cues	Mirroring non-verbal social cues such as affect or movement can enhance human-human and human-robot interactions in the real world. The robotic platforms and control methods also impact people's perception of human-robot interaction. However, limited studies have compared robot imitation across different platforms and ...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	423,250
2202.00243	Adversarial Imitation Learning from Video using a State Observer	The imitation learning research community has recently made significant progress towards the goal of enabling artificial agents to imitate behaviors from video demonstrations alone. However, current state-of-the-art approaches developed for this problem exhibit high sample complexity due, in part, to the high-dimension...	false	false	false	false	true	false	true	true	false	false	true	true	false	false	false	false	false	false	278,077
2403.11667	Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection	The high performance of denoising diffusion models for image generation has paved the way for their application in unsupervised medical anomaly detection. As diffusion-based methods require a lot of GPU memory and have long sampling times, we present a novel and fast unsupervised anomaly detection approach based on lat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,804
2303.11859	LEAPS: End-to-End One-Step Person Search With Learnable Proposals	We propose an end-to-end one-step person search approach with learnable proposals, named LEAPS. Given a set of sparse and learnable proposals, LEAPS employs a dynamic person search head to directly perform person detection and corresponding re-id feature generation without non-maximum suppression post-processing. The d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	353,038
2106.03645	Photonic Differential Privacy with Direct Feedback Alignment	Optical Processing Units (OPUs) -- low-power photonic chips dedicated to large scale random projections -- have been used in previous work to train deep neural networks using Direct Feedback Alignment (DFA), an effective alternative to backpropagation. Here, we demonstrate how to leverage the intrinsic noise of optical...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	239,394
1810.02789	Doubly Semi-Implicit Variational Inference	We extend the existing framework of semi-implicit variational inference (SIVI) and introduce doubly semi-implicit variational inference (DSIVI), a way to perform variational inference and learning when both the approximate posterior and the prior distribution are semi-implicit. In other words, DSIVI performs inference ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,660
2203.08928	C-MORE: Pretraining to Answer Open-Domain Questions by Consulting Millions of References	We consider the problem of pretraining a two-stage open-domain question answering (QA) system (retriever + reader) with strong transfer capabilities. The key challenge is how to construct a large amount of high-quality question-answer-context triplets without task-specific annotations. Specifically, the triplets should...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	285,954
2307.01316	Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning Approach	The dynamic nature of driving environments and the presence of diverse road users pose significant challenges for decision-making in autonomous driving. Deep reinforcement learning (DRL) has emerged as a popular approach to tackle this problem. However, the application of existing DRL solutions is mainly confined to si...	false	false	false	false	true	false	true	true	false	false	true	false	false	false	false	false	false	true	377,308
1601.01614	Toward Organic Computing Approach for Cybernetic Responsive Environment	The developpment of the Internet of Things (IoT) concept revives Responsive Environments (RE) technologies. Nowadays, the idea of a permanent connection between physical and digital world is technologically possible. The capillar Internet relates to the Internet extension into daily appliances such as they become actor...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	50,764
2002.12776	ResNets, NeuralODEs and CT-RNNs are Particular Neural Regulatory Networks	This paper shows that ResNets, NeuralODEs, and CT-RNNs, are particular neural regulatory networks (NRNs), a biophysical model for the nonspiking neurons encountered in small species, such as the C.elegans nematode, and in the retina of large species. Compared to ResNets, NeuralODEs and CT-RNNs, NRNs have an additional ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	166,133
2407.09551	Diminishing Stereotype Bias in Image Generation Model using Reinforcemenlent Learning Feedback	This study addresses gender bias in image generation models using Reinforcement Learning from Artificial Intelligence Feedback (RLAIF) with a novel Denoising Diffusion Policy Optimization (DDPO) pipeline. By employing a pretrained stable diffusion model and a highly accurate gender classification Transformer, the resea...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	472,639
2405.10133	Turkronicles: Diachronic Resources for the Fast Evolving Turkish Language	Over the past century, the Turkish language has undergone substantial changes, primarily driven by governmental interventions. In this work, our goal is to investigate the evolution of the Turkish language since the establishment of T\"urkiye in 1923. Thus, we first introduce Turkronicles which is a diachronic corpus f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	454,655
1802.02049	A Distance Between Channels: the average error of mismatched channels	Two channels are equivalent if their maximum likelihood (ML) decoders coincide for every code. We show that this equivalence relation partitions the space of channels into a generalized hyperplane arrangement. With this, we define a coding distance between channels in terms of their ML-decoders which is meaningful from...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	89,694
2403.01605	Towards Provable Log Density Policy Gradient	Policy gradient methods are a vital ingredient behind the success of modern reinforcement learning. Modern policy gradient methods, although successful, introduce a residual error in gradient estimation. In this work, we argue that this residual term is significant and correcting for it could potentially improve sample...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	434,496
1711.06426	Towards Self-organized Large-Scale Shape Formation: A Cognitive Agent-Based Computing Approach	Swarm robotic systems are currently being used to address many real-world problems. One interesting application of swarm robotics is the self-organized formation of structures and shapes. Some of the key challenges in the swarm robotic systems include swarm size constraint, random motion, coordination among robots, loc...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	84,766
1207.4813	Exploring the rationality of some syntactic merging operators (extended version)	Most merging operators are defined by semantics methods which have very high computational complexity. In order to have operators with a lower computational complexity, some merging operators defined in a syntactical way have be proposed. In this work we define some syntactical merging operators and exploring its ratio...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	17,670
1901.03155	Entropy Bounds for Grammar-Based Tree Compressors	The definition of $k^{th}$-order empirical entropy of strings is extended to node labelled binary trees. A suitable binary encoding of tree straight-line programs (that have been used for grammar-based tree compression before) is shown to yield binary tree encodings of size bounded by the $k^{th}$-order empirical entro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	118,353
1710.07480	HDR image reconstruction from a single exposure using deep CNNs	Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combined. In this paper we address the problem of predicting information that have been lost in saturated image areas, in order to enable HDR rec...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	82,946
2407.10461	Multibeam Satellite Communications with Massive MIMO: Asymptotic Performance Analysis and Design Insights	To achieve high performance without substantial overheads associated with channel state information (CSI) of ground users, we consider a fixed-beam precoding approach, where a satellite forms multiple fixed-beams without relying on CSI, then select a suitable user set for each beam. Upon this precoding method, we put f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	472,999

Subsets and Splits

No community queries yet

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