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
2209.12110	Answer-Set Programs for Repair Updates and Counterfactual Interventions	We briefly describe -- mainly through very simple examples -- different kinds of answer-set programs with annotations that have been proposed for specifying: database repairs and consistent query answering; secrecy view and query evaluation with them; counterfactual interventions for causality in databases; and counter...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	true	319,423
2308.03409	DiT: Efficient Vision Transformers with Dynamic Token Routing	Recently, the tokens of images share the same static data flow in many dense networks. However, challenges arise from the variance among the objects in images, such as large variations in the spatial scale and difficulties of recognition for visual entities. In this paper, we propose a data-dependent token routing stra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	384,028
2103.00988	Moment-Based Variational Inference for Stochastic Differential Equations	Existing deterministic variational inference approaches for diffusion processes use simple proposals and target the marginal density of the posterior. We construct the variational process as a controlled version of the prior process and approximate the posterior by a set of moment functions. In combination with moment ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	222,476
2307.16256	3D Medical Image Segmentation with Sparse Annotation via Cross-Teaching between 3D and 2D Networks	Medical image segmentation typically necessitates a large and precisely annotated dataset. However, obtaining pixel-wise annotation is a labor-intensive task that requires significant effort from domain experts, making it challenging to obtain in practical clinical scenarios. In such situations, reducing the amount of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	382,542
2301.11802	Decentralized Online Bandit Optimization on Directed Graphs with Regret Bounds	We consider a decentralized multiplayer game, played over $T$ rounds, with a leader-follower hierarchy described by a directed acyclic graph. For each round, the graph structure dictates the order of the players and how players observe the actions of one another. By the end of each round, all players receive a joint ba...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	342,281
2303.14488	Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images	Object detection on drone images with low-latency is an important but challenging task on the resource-constrained unmanned aerial vehicle (UAV) platform. This paper investigates optimizing the detection head based on the sparse convolution, which proves effective in balancing the accuracy and efficiency. Nevertheless,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,118
2103.14431	Multimodal Knowledge Expansion	The popularity of multimodal sensors and the accessibility of the Internet have brought us a massive amount of unlabeled multimodal data. Since existing datasets and well-trained models are primarily unimodal, the modality gap between a unimodal network and unlabeled multimodal data poses an interesting problem: how to...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	226,857
2401.08149	Channel Estimation for Holographic Communications in Hybrid Near-Far Field	To realize holographic communications, a potential technology for spectrum efficiency improvement in the future sixth-generation (6G) network, antenna arrays inlaid with numerous antenna elements will be deployed. However, the increase in antenna aperture size makes some users lie in the Fresnel region, leading to the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	421,784
2112.04329	JABER and SABER: Junior and Senior Arabic BERt	Language-specific pre-trained models have proven to be more accurate than multilingual ones in a monolingual evaluation setting, Arabic is no exception. However, we found that previously released Arabic BERT models were significantly under-trained. In this technical report, we present JABER and SABER, Junior and Senior...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	270,491
2401.12254	Transfer learning-assisted inverse modeling in nanophotonics based on mixture density networks	The simulation of nanophotonic structures relies on electromagnetic solvers, which play a crucial role in understanding their behavior. However, these solvers often come with a significant computational cost, making their application in design tasks, such as optimization, impractical. To address this challenge, machine...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	423,322
2406.10100	SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding	Remote Sensing Large Multi-Modal Models (RSLMMs) are developing rapidly and showcase significant capabilities in remote sensing imagery (RSI) comprehension. However, due to the limitations of existing datasets, RSLMMs have shortcomings in understanding the rich semantic relations among objects in complex remote sensing...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	464,225
2110.07137	A CLIP-Enhanced Method for Video-Language Understanding	This technical report summarizes our method for the Video-And-Language Understanding Evaluation (VALUE) challenge (https://value-benchmark.github.io/challenge\_2021.html). We propose a CLIP-Enhanced method to incorporate the image-text pretrained knowledge into downstream video-text tasks. Combined with several other i...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	260,873
1702.04466	Guess & Check Codes for Deletions and Synchronization	We consider the problem of constructing codes that can correct $\delta$ deletions occurring in an arbitrary binary string of length $n$ bits. Varshamov-Tenengolts (VT) codes can correct all possible single deletions $(\delta=1)$ with an asymptotically optimal redundancy. Finding similar codes for $\delta \geq 2$ deleti...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,262
2201.08383	MeMViT: Memory-Augmented Multiscale Vision Transformer for Efficient Long-Term Video Recognition	While today's video recognition systems parse snapshots or short clips accurately, they cannot connect the dots and reason across a longer range of time yet. Most existing video architectures can only process <5 seconds of a video without hitting the computation or memory bottlenecks. In this paper, we propose a new ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	276,322
2402.05554	One-Stop Automated Diagnostic System for Carpal Tunnel Syndrome in Ultrasound Images Using Deep Learning	Objective: Ultrasound (US) examination has unique advantages in diagnosing carpal tunnel syndrome (CTS) while identifying the median nerve (MN) and diagnosing CTS depends heavily on the expertise of examiners. To alleviate this problem, we aimed to develop a one-stop automated CTS diagnosis system (OSA-CTSD) and evalua...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	427,905
2304.13178	Robust Non-Linear Feedback Coding via Power-Constrained Deep Learning	The design of codes for feedback-enabled communications has been a long-standing open problem. Recent research on non-linear, deep learning-based coding schemes have demonstrated significant improvements in communication reliability over linear codes, but are still vulnerable to the presence of forward and feedback noi...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	360,490
2411.10606	AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment	Motivated by the transformative capabilities of large language models (LLMs) across various natural language tasks, there has been a growing demand to deploy these models effectively across diverse real-world applications and platforms. However, the challenge of efficiently deploying LLMs has become increasingly pronou...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	508,712
1203.1869	Degraded Broadcast Diamond Channels with Non-Causal State Information at the Source	A state-dependent degraded broadcast diamond channel is studied where the source-to-relays cut is modeled with two noiseless, finite-capacity digital links with a degraded broadcasting structure, while the relays-to-destination cut is a general multiple access channel controlled by a random state. It is assumed that th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,793
2002.03788	Generating diverse and natural text-to-speech samples using a quantized fine-grained VAE and auto-regressive prosody prior	Recent neural text-to-speech (TTS) models with fine-grained latent features enable precise control of the prosody of synthesized speech. Such models typically incorporate a fine-grained variational autoencoder (VAE) structure, extracting latent features at each input token (e.g., phonemes). However, generating samples ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	163,408
1802.06933	AMC and HARQ: How to Increase the Throughput	In this work, we consider transmissions over block fading channels and assume that adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) are implemented. Knowing that in high signal-to-noise ratio, the conventional combination of HARQ with AMC is counterproductive from the throughput point of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	90,786
1512.02970	Efficient Distributed SGD with Variance Reduction	Stochastic Gradient Descent (SGD) has become one of the most popular optimization methods for training machine learning models on massive datasets. However, SGD suffers from two main drawbacks: (i) The noisy gradient updates have high variance, which slows down convergence as the iterates approach the optimum, and (ii)...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	49,986
1304.7018	Higher-order compatible discretization on hexahedrals	We derive a compatible discretization method that relies heavily on the underlying geometric structure, and obeys the topological sequences and commuting properties that are constructed. As a sample problem we consider the vorticity-velocity-pressure formulation of the Stokes problem. We motivate the choice for a mixed...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	24,213
2404.00485	DiffHuman: Probabilistic Photorealistic 3D Reconstruction of Humans	We present DiffHuman, a probabilistic method for photorealistic 3D human reconstruction from a single RGB image. Despite the ill-posed nature of this problem, most methods are deterministic and output a single solution, often resulting in a lack of geometric detail and blurriness in unseen or uncertain regions. In cont...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	442,949
2012.13319	Toward the use of temporary tattoo electrodes for impedancemetric respiration monitoring and other electrophysiological recordings	Development of dry, ultra-conformable and unperceivable temporary tattoo electrodes (TTEs), based on the ink-jet printing of PEDOT:PSS on top of commercially available temporary tattoo paper, has gained increasing attention as a new and promising technology for electrophysiological recordings on skin. In this work we p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	213,185
2311.17871	Estimation of Dynamic Gaussian Processes	Gaussian processes provide a compact representation for modeling and estimating an unknown function, that can be updated as new measurements of the function are obtained. This paper extends this powerful framework to the case where the unknown function dynamically changes over time. Specifically, we assume that the fun...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	411,447
1310.1404	Sequential Monte Carlo Bandits	In this paper we propose a flexible and efficient framework for handling multi-armed bandits, combining sequential Monte Carlo algorithms with hierarchical Bayesian modeling techniques. The framework naturally encompasses restless bandits, contextual bandits, and other bandit variants under a single inferential model. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	27,565
2410.21481	A Mathematical Analysis of Neural Operator Behaviors	Neural operators have emerged as transformative tools for learning mappings between infinite-dimensional function spaces, offering useful applications in solving complex partial differential equations (PDEs). This paper presents a rigorous mathematical framework for analyzing the behaviors of neural operators, with a f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	503,262
2209.09493	A framework for benchmarking clustering algorithms	The evaluation of clustering algorithms can involve running them on a variety of benchmark problems, and comparing their outputs to the reference, ground-truth groupings provided by experts. Unfortunately, many research papers and graduate theses consider only a small number of datasets. Also, the fact that there can b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	318,535
cs/0606020	Imagination as Holographic Processor for Text Animation	Imagination is the critical point in developing of realistic artificial intelligence (AI) systems. One way to approach imagination would be simulation of its properties and operations. We developed two models: AI-Brain Network Hierarchy of Languages and Semantical Holographic Calculus as well as simulation system Scrip...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	539,505
1508.01292	Compact Convolutional Neural Network Cascade for Face Detection	The problem of faces detection in images or video streams is a classical problem of computer vision. The multiple solutions of this problem have been proposed, but the question of their optimality is still open. Many algorithms achieve a high quality face detection, but at the cost of high computational complexity. Thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,773
0707.1025	The star trellis decoding of Reed-Solomon codes	The new method for Reed-Solomon codes decoding is introduced. The method is based on the star trellis decoding of the binary image of Reed-Solomon codes.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	402
2211.07912	YORO -- Lightweight End to End Visual Grounding	We present YORO - a multi-modal transformer encoder-only architecture for the Visual Grounding (VG) task. This task involves localizing, in an image, an object referred via natural language. Unlike the recent trend in the literature of using multi-stage approaches that sacrifice speed for accuracy, YORO seeks a better ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	330,414
1602.04921	A diffusion and clustering-based approach for finding coherent motions and understanding crowd scenes	This paper addresses the problem of detecting coherent motions in crowd scenes and presents its two applications in crowd scene understanding: semantic region detection and recurrent activity mining. It processes input motion fields (e.g., optical flow fields) and produces a coherent motion filed, named as thermal ener...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	52,196
2410.01154	Unleashing the Power of Large Language Models in Zero-shot Relation Extraction via Self-Prompting	Recent research in zero-shot Relation Extraction (RE) has focused on using Large Language Models (LLMs) due to their impressive zero-shot capabilities. However, current methods often perform suboptimally, mainly due to a lack of detailed, context-specific prompts needed for understanding various sentences and relations...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	493,633
2303.11574	Bounding System-Induced Biases in Recommender Systems with A Randomized Dataset	Debiased recommendation with a randomized dataset has shown very promising results in mitigating the system-induced biases. However, it still lacks more theoretical insights or an ideal optimization objective function compared with the other more well studied route without a randomized dataset. To bridge this gap, we s...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	352,905
2105.12555	Context-aware Cross-level Fusion Network for Camouflaged Object Detection	Camouflaged object detection (COD) is a challenging task due to the low boundary contrast between the object and its surroundings. In addition, the appearance of camouflaged objects varies significantly, e.g., object size and shape, aggravating the difficulties of accurate COD. In this paper, we propose a novel Context...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	237,041
2502.01145	Tackling Feature and Sample Heterogeneity in Decentralized Multi-Task Learning: A Sheaf-Theoretic Approach	Federated multi-task learning (FMTL) aims to simultaneously learn multiple related tasks across clients without sharing sensitive raw data. However, in the decentralized setting, existing FMTL frameworks are limited in their ability to capture complex task relationships and handle feature and sample heterogeneity acros...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	529,717
2410.06555	ING-VP: MLLMs cannot Play Easy Vision-based Games Yet	As multimodal large language models (MLLMs) continue to demonstrate increasingly competitive performance across a broad spectrum of tasks, more intricate and comprehensive benchmarks have been developed to assess these cutting-edge models. These benchmarks introduce new challenges to core capabilities such as perceptio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	496,261
1712.01662	Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data	Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with inte...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	86,147
2111.00440	Loop closure detection using local 3D deep descriptors	We present a simple yet effective method to address loop closure detection in simultaneous localisation and mapping using local 3D deep descriptors (L3Ds). L3Ds are emerging compact representations of patches extracted from point clouds that are learnt from data using a deep learning algorithm. We propose a novel overl...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	264,221
2409.19700	2D-TPE: Two-Dimensional Positional Encoding Enhances Table Understanding for Large Language Models	Tables are ubiquitous across various domains for concisely representing structured information. Empowering large language models (LLMs) to reason over tabular data represents an actively explored direction. However, since typical LLMs only support one-dimensional~(1D) inputs, existing methods often flatten the two-dime...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	492,809
2207.02597	Cooperative Beam Selection for RIS-Aided Terahertz MIMO Networks via Multi-Task Learning	Reconfigurable intelligent surface (RIS) have been cast as a promising alternative to alleviate blockage vulnerability and enhance coverage capability for terahertz (THz) communications. Owing to large-scale array elements at transceivers and RIS, the codebook based beamforming can be utilized in a computationally effi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	306,565
2003.12223	Secure network code over one-hop relay network	When there exists a malicious attacker in the network, we need to consider the possibilities of eavesdropping and the contamination simultaneously. Under an acyclic broadcast network, the optimality of linear codes was shown when Eve is allowed to attack any $r$ edges. The optimality of linear codes is not shown under ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	169,853
1501.02475	Teleoperando Rob\^os Pioneer Utilizando Android	This paper presents an application with ROS, Aria and RosAria to control a ModelSim simulated Pioneer 3-DX robot. The navigation applies a simple autonomous algorithm and a teleoperation control using an Android device sending the gyroscope generated information.	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	39,189
2408.00802	Leveraging LLM Reasoning Enhances Personalized Recommender Systems	Recent advancements have showcased the potential of Large Language Models (LLMs) in executing reasoning tasks, particularly facilitated by Chain-of-Thought (CoT) prompting. While tasks like arithmetic reasoning involve clear, definitive answers and logical chains of thought, the application of LLM reasoning in recommen...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	477,994
1508.07527	Combining exome and gene expression datasets in one graphical model of disease to empower the discovery of disease mechanisms	Identifying genes associated with complex human diseases is one of the main challenges of human genetics and computational medicine. To answer this question, millions of genetic variants get screened to identify a few of importance. To increase the power of identifying genes associated with diseases and to account for ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	46,410
2404.06681	Causal Unit Selection using Tractable Arithmetic Circuits	The unit selection problem aims to find objects, called units, that optimize a causal objective function which describes the objects' behavior in a causal context (e.g., selecting customers who are about to churn but would most likely change their mind if encouraged). While early studies focused mainly on bounding a sp...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	445,554
2410.21794	Inverse Attention Agent for Multi-Agent System	A major challenge for Multi-Agent Systems is enabling agents to adapt dynamically to diverse environments in which opponents and teammates may continually change. Agents trained using conventional methods tend to excel only within the confines of their training cohorts; their performance drops significantly when confro...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	503,392
2406.09030	CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms	The utilization of the experience replay mechanism enables agents to effectively leverage their experiences on several occasions. In previous studies, the sampling probability of the transitions was modified based on their relative significance. The process of reassigning sample probabilities for every transition in th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	463,732
1102.3396	Detecting Separation in Robotic and Sensor Networks	In this paper we consider the problem of monitoring detecting separation of agents from a base station in robotic and sensor networks. Such separation can be caused by mobility and/or failure of the agents. While separation/cut detection may be performed by passing messages between a node and the base in static network...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	9,244
2406.12909	Scalable Training of Trustworthy and Energy-Efficient Predictive Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN	We present our work on developing and training scalable, trustworthy, and energy-efficient predictive graph foundation models (GFMs) using HydraGNN, a multi-headed graph convolutional neural network architecture. HydraGNN expands the boundaries of graph neural network (GNN) computations in both training scale and data ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	465,618
1407.6823	Measuring Prestige in Online Social Networks	We study the locally-defined social capital metric of Palasek (2013) for determining individuals' prestige within an online social network. From it we derive an equivalent global measure by considering random walks over the network itself. This result inspires a novel expression quantifying the strategic desirability o...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	34,894
2501.15385	DDUNet: Dual Dynamic U-Net for Highly-Efficient Cloud Segmentation	Cloud segmentation amounts to separating cloud pixels from non-cloud pixels in an image. Current deep learning methods for cloud segmentation suffer from three issues. (a) Constrain on their receptive field due to the fixed size of the convolution kernel. (b) Lack of robustness towards different scenarios. (c) Requirem...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	527,528
2210.15513	Lifelong Bandit Optimization: No Prior and No Regret	Machine learning algorithms are often repeatedly applied to problems with similar structure over and over again. We focus on solving a sequence of bandit optimization tasks and develop LIBO, an algorithm which adapts to the environment by learning from past experience and becomes more sample-efficient in the process. W...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	326,989
1501.01779	Reviving the Two-state Markov Chain Approach (Technical Report)	Probabilistic Boolean networks (PBNs) is a well-established computational framework for modelling biological systems. The steady-state dynamics of PBNs is of crucial importance in the study of such systems. However, for large PBNs, which often arise in systems biology, obtaining the steady-state distribution poses a si...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	39,121
1912.05752	The Use of Deep Learning for Symbolic Integration: A Review of (Lample and Charton, 2019)	Lample and Charton (2019) describe a system that uses deep learning technology to compute symbolic, indefinite integrals, and to find symbolic solutions to first- and second-order ordinary differential equations, when the solutions are elementary functions. They found that, over a particular test set, the system could ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	157,184
1205.6352	Generalized sequential tree-reweighted message passing	This paper addresses the problem of approximate MAP-MRF inference in general graphical models. Following [36], we consider a family of linear programming relaxations of the problem where each relaxation is specified by a set of nested pairs of factors for which the marginalization constraint needs to be enforced. We de...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	16,218
2105.11856	Spectrum Correction: Acoustic Scene Classification with Mismatched Recording Devices	Machine learning algorithms, when trained on audio recordings from a limited set of devices, may not generalize well to samples recorded using other devices with different frequency responses. In this work, a relatively straightforward method is introduced to address this problem. Two variants of the approach are prese...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	236,843
1702.03040	Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities	The follow the leader (FTL) algorithm, perhaps the simplest of all online learning algorithms, is known to perform well when the loss functions it is used on are convex and positively curved. In this paper we ask whether there are other "lucky" settings when FTL achieves sublinear, "small" regret. In particular, we stu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	68,068
2304.08743	Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control with Action Constraints	This study presents a benchmark for evaluating action-constrained reinforcement learning (RL) algorithms. In action-constrained RL, each action taken by the learning system must comply with certain constraints. These constraints are crucial for ensuring the feasibility and safety of actions in real-world systems. We ev...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	358,801
2204.03648	SunStage: Portrait Reconstruction and Relighting using the Sun as a Light Stage	A light stage uses a series of calibrated cameras and lights to capture a subject's facial appearance under varying illumination and viewpoint. This captured information is crucial for facial reconstruction and relighting. Unfortunately, light stages are often inaccessible: they are expensive and require significant te...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	290,386
2412.16423	Technical Report: Small Language Model for Japanese Clinical and Medicine	This report presents a small language model (SLM) for Japanese clinical and medicine, named NCVC-slm-1. This 1B parameters model was trained using Japanese text classified to be of high-quality. Moreover, NCVC-slm-1 was augmented with respect to clinical and medicine content that includes the variety of diseases, drugs...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	519,508
2307.09896	Repeated Observations for Classification	We study the problem nonparametric classification with repeated observations. Let $\bX$ be the $d$ dimensional feature vector and let $Y$ denote the label taking values in $\{1,\dots ,M\}$. In contrast to usual setup with large sample size $n$ and relatively low dimension $d$, this paper deals with the situation, when ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	380,342
2207.05757	Robust and efficient computation of retinal fractal dimension through deep approximation	A retinal trait, or phenotype, summarises a specific aspect of a retinal image in a single number. This can then be used for further analyses, e.g. with statistical methods. However, reducing an aspect of a complex image to a single, meaningful number is challenging. Thus, methods for calculating retinal traits tend to...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	307,657
2401.07240	DCDet: Dynamic Cross-based 3D Object Detector	Recently, significant progress has been made in the research of 3D object detection. However, most prior studies have focused on the utilization of center-based or anchor-based label assignment schemes. Alternative label assignment strategies remain unexplored in 3D object detection. We find that the center-based label...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	421,466
1709.07848	Multiqubit and multilevel quantum reinforcement learning with quantum technologies	We propose a protocol to perform quantum reinforcement learning with quantum technologies. At variance with recent results on quantum reinforcement learning with superconducting circuits, in our current protocol coherent feedback during the learning process is not required, enabling its implementation in a wide variety...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	81,351
2309.00236	Image Hijacks: Adversarial Images can Control Generative Models at Runtime	Are foundation models secure against malicious actors? In this work, we focus on the image input to a vision-language model (VLM). We discover image hijacks, adversarial images that control the behaviour of VLMs at inference time, and introduce the general Behaviour Matching algorithm for training image hijacks. From t...	false	false	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	389,238
2402.13393	Fairness Risks for Group-conditionally Missing Demographics	Fairness-aware classification models have gained increasing attention in recent years as concerns grow on discrimination against some demographic groups. Most existing models require full knowledge of the sensitive features, which can be impractical due to privacy, legal issues, and an individual's fear of discriminati...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	431,218
1507.04642	Resolving Multi-party Privacy Conflicts in Social Media	Items shared through Social Media may affect more than one user's privacy --- e.g., photos that depict multiple users, comments that mention multiple users, events in which multiple users are invited, etc. The lack of multi-party privacy management support in current mainstream Social Media infrastructures makes users ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	45,202
2206.01512	Latent Topology Induction for Understanding Contextualized Representations	In this work, we study the representation space of contextualized embeddings and gain insight into the hidden topology of large language models. We show there exists a network of latent states that summarize linguistic properties of contextualized representations. Instead of seeking alignments to existing well-defined ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	true	false	false	300,502
1407.0316	Significant Subgraph Mining with Multiple Testing Correction	The problem of finding itemsets that are statistically significantly enriched in a class of transactions is complicated by the need to correct for multiple hypothesis testing. Pruning untestable hypotheses was recently proposed as a strategy for this task of significant itemset mining. It was shown to lead to greater s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	34,317
2005.14346	Consistent Second-Order Conic Integer Programming for Learning Bayesian Networks	Bayesian Networks (BNs) represent conditional probability relations among a set of random variables (nodes) in the form of a directed acyclic graph (DAG), and have found diverse applications in knowledge discovery. We study the problem of learning the sparse DAG structure of a BN from continuous observational data. The...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	179,241
1402.5750	A new inexact iterative hard thresholding algorithm for compressed sensing	Compressed sensing (CS) demonstrates that a sparse, or compressible signal can be acquired using a low rate acquisition process below the Nyquist rate, which projects the signal onto a small set of vectors incoherent with the sparsity basis. In this paper, we propose a new framework for compressed sensing recovery prob...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	31,105
2208.14883	Binary Representation via Jointly Personalized Sparse Hashing	Unsupervised hashing has attracted much attention for binary representation learning due to the requirement of economical storage and efficiency of binary codes. It aims to encode high-dimensional features in the Hamming space with similarity preservation between instances. However, most existing methods learn hash fun...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	315,448
2102.00689	A NIR-to-VIS face recognition via part adaptive and relation attention module	In the face recognition application scenario, we need to process facial images captured in various conditions, such as at night by near-infrared (NIR) surveillance cameras. The illumination difference between NIR and visible-light (VIS) causes a domain gap between facial images, and the variations in pose and emotion a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	217,881
2008.13482	FunMap: Efficient Execution of Functional Mappings for Knowledge Graph Creation	Data has exponentially grown in the last years, and knowledge graphs constitute powerful formalisms to integrate a myriad of existing data sources. Transformation functions -- specified with function-based mapping languages like FunUL and RML+FnO -- can be applied to overcome interoperability issues across heterogeneou...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	193,853
2308.04539	Improving Performance in Continual Learning Tasks using Bio-Inspired Architectures	The ability to learn continuously from an incoming data stream without catastrophic forgetting is critical to designing intelligent systems. Many approaches to continual learning rely on stochastic gradient descent and its variants that employ global error updates, and hence need to adopt strategies such as memory buff...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	384,450
2103.10773	UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning	Momentum Contrast (MoCo) achieves great success for unsupervised visual representation. However, there are a lot of supervised and semi-supervised datasets, which are already labeled. To fully utilize the label annotations, we propose Unified Momentum Contrast (UniMoCo), which extends MoCo to support arbitrary ratios o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	225,565
2402.10855	Control Color: Multimodal Diffusion-based Interactive Image Colorization	Despite the existence of numerous colorization methods, several limitations still exist, such as lack of user interaction, inflexibility in local colorization, unnatural color rendering, insufficient color variation, and color overflow. To solve these issues, we introduce Control Color (CtrlColor), a multi-modal colori...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	430,141
2402.03660	On the Emergence of Cross-Task Linearity in the Pretraining-Finetuning Paradigm	The pretraining-finetuning paradigm has become the prevailing trend in modern deep learning. In this work, we discover an intriguing linear phenomenon in models that are initialized from a common pretrained checkpoint and finetuned on different tasks, termed as Cross-Task Linearity (CTL). Specifically, we show that if ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	427,122
2011.07325	Sparsity-Inducing Optimal Control via Differential Dynamic Programming	Optimal control is a popular approach to synthesize highly dynamic motion. Commonly, $L_2$ regularization is used on the control inputs in order to minimize energy used and to ensure smoothness of the control inputs. However, for some systems, such as satellites, the control needs to be applied in sparse bursts due to ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	206,512
2306.03506	Subgraph Networks Based Contrastive Learning	Graph contrastive learning (GCL), as a self-supervised learning method, can solve the problem of annotated data scarcity. It mines explicit features in unannotated graphs to generate favorable graph representations for downstream tasks. Most existing GCL methods focus on the design of graph augmentation strategies and ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	371,361
2208.00716	Graph Neural Network with Local Frame for Molecular Potential Energy Surface	Modeling molecular potential energy surface is of pivotal importance in science. Graph Neural Networks have shown great success in this field. However, their message passing schemes need special designs to capture geometric information and fulfill symmetry requirement like rotation equivariance, leading to complicated ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	310,938
2309.01350	MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware	Malware is one of the most dangerous and costly cyber threats to national security and a crucial factor in modern cyber-space. However, the adoption of machine learning (ML) based solutions against malware threats has been relatively slow. Shortcomings in the existing ML approaches are likely contributing to this probl...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	389,651
cs/0611138	Functional Brain Imaging with Multi-Objective Multi-Modal Evolutionary Optimization	Functional brain imaging is a source of spatio-temporal data mining problems. A new framework hybridizing multi-objective and multi-modal optimization is proposed to formalize these data mining problems, and addressed through Evolutionary Computation (EC). The merits of EC for spatio-temporal data mining are demonstrat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	539,917
0903.1850	Free actions and Grassmanian variety	An algebraic notion of representational consistency is defined. A theorem relating it to free actions is proved. A metrizability problem of the quotient (a shape space) is discussed. This leads to a new algebraic variety with a metrizability result. A concrete example is given from stereo vision.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	3,327
2011.08800	Tensor-Decomposition-based Hybrid Beamforming Design for mmWave OFDM Massive MIMO Communications	In this paper, we propose a novel joint hybrid precoder and combiner design for maximizing the average achievable sum-rate of single-user orthogonal frequency division multiplexing millimeter wave massive MIMO systems. We formulate the analog precoder and combiner design as a constrained Tucker2 decomposition and solve...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	206,999
2105.11066	Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence	Policy optimization, which finds the desired policy by maximizing value functions via optimization techniques, lies at the heart of reinforcement learning (RL). In addition to value maximization, other practical considerations arise as well, including the need of encouraging exploration, and that of ensuring certain st...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	236,583
2001.03608	Solving inverse-PDE problems with physics-aware neural networks	We propose a novel composite framework to find unknown fields in the context of inverse problems for partial differential equations (PDEs). We blend the high expressibility of deep neural networks as universal function estimators with the accuracy and reliability of existing numerical algorithms for partial differentia...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	160,019
2402.07790	From Uncertainty to Precision: Enhancing Binary Classifier Performance through Calibration	The assessment of binary classifier performance traditionally centers on discriminative ability using metrics, such as accuracy. However, these metrics often disregard the model's inherent uncertainty, especially when dealing with sensitive decision-making domains, such as finance or healthcare. Given that model-predic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	428,848
2307.15942	CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation	Most nighttime semantic segmentation studies are based on domain adaptation approaches and image input. However, limited by the low dynamic range of conventional cameras, images fail to capture structural details and boundary information in low-light conditions. Event cameras, as a new form of vision sensors, are compl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	382,420
2112.02195	Revisiting local branching with a machine learning lens	Finding high-quality solutions to mixed-integer linear programming problems (MILPs) is of great importance for many practical applications. In this respect, the refinement heuristic local branching (LB) has been proposed to produce improving solutions and has been highly influential for the development of local search ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	269,754
2411.12597	GNNAS-Dock: Budget Aware Algorithm Selection with Graph Neural Networks for Molecular Docking	Molecular docking is a major element in drug discovery and design. It enables the prediction of ligand-protein interactions by simulating the binding of small molecules to proteins. Despite the availability of numerous docking algorithms, there is no single algorithm consistently outperforms the others across a diverse...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	509,464
2411.17014	Entropy-Based Dynamic Programming for Efficient Vehicle Parking	In urban environments, parking has proven to be a significant source of congestion and inefficiency. In this study, we propose a methodology that offers a systematic solution to minimize the time spent by drivers in finding parking spaces. Drawing inspiration from statistical mechanics, we utilize an entropy model to p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	511,272
2102.07865	Large Deviations Principle for Discrete-time Mean-field Games	In this paper, we establish a large deviations principle (LDP) for interacting particle systems that arise from state and action dynamics of discrete-time mean-field games under the equilibrium policy of the infinite-population limit. The LDP is proved under weak Feller continuity of state and action dynamics. The proo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	220,256
2409.11836	NT-ViT: Neural Transcoding Vision Transformers for EEG-to-fMRI Synthesis	This paper introduces the Neural Transcoding Vision Transformer (\modelname), a generative model designed to estimate high-resolution functional Magnetic Resonance Imaging (fMRI) samples from simultaneous Electroencephalography (EEG) data. A key feature of \modelname is its Domain Matching (DM) sub-module which effecti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	489,337
1904.04360	Optimizing Majority Voting Based Systems Under a Resource Constraint for Multiclass Problems	Ensemble-based approaches are very effective in various fields in raising the accuracy of its individual members, when some voting rule is applied for aggregating the individual decisions. In this paper, we investigate how to find and characterize the ensembles having the highest accuracy if the total cost of the ensem...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	127,010
2106.06147	NAAQA: A Neural Architecture for Acoustic Question Answering	The goal of the Acoustic Question Answering (AQA) task is to answer a free-form text question about the content of an acoustic scene. It was inspired by the Visual Question Answering (VQA) task. In this paper, based on the previously introduced CLEAR dataset, we propose a new benchmark for AQA, namely CLEAR2, that emph...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	240,378
2311.01717	Second-Order Convergent Collision-Constrained Optimization-Based Planner	Finding robot poses and trajectories represents a foundational aspect of robot motion planning. Despite decades of research, efficiently and robustly addressing these challenges is still difficult. Existing approaches are often plagued by various limitations, such as intricate geometric approximations, violations of co...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	405,146
1902.01955	On the Choice of Modeling Unit for Sequence-to-Sequence Speech Recognition	In conventional speech recognition, phoneme-based models outperform grapheme-based models for non-phonetic languages such as English. The performance gap between the two typically reduces as the amount of training data is increased. In this work, we examine the impact of the choice of modeling unit for attention-based ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	120,774

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