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
2003.13853	Semi-supervised Learning for Few-shot Image-to-Image Translation	In the last few years, unpaired image-to-image translation has witnessed remarkable progress. Although the latest methods are able to generate realistic images, they crucially rely on a large number of labeled images. Recently, some methods have tackled the challenging setting of few-shot image-to-image translation, re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	170,328
2107.08662	A Queueing-Theoretic Framework for Vehicle Dispatching in Dynamic Car-Hailing [technical report]	With the rapid development of smart mobile devices, the car-hailing platforms (e.g., Uber or Lyft) have attracted much attention from both the academia and the industry. In this paper, we consider an important dynamic car-hailing problem, namely \textit{maximum revenue vehicle dispatching} (MRVD), in which rider reques...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	246,798
2102.11391	MagNet: A Neural Network for Directed Graphs	The prevalence of graph-based data has spurred the rapid development of graph neural networks (GNNs) and related machine learning algorithms. Yet, despite the many datasets naturally modeled as directed graphs, including citation, website, and traffic networks, the vast majority of this research focuses on undirected g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	221,401
2012.01721	Learning Class-Transductive Intent Representations for Zero-shot Intent Detection	Zero-shot intent detection (ZSID) aims to deal with the continuously emerging intents without annotated training data. However, existing ZSID systems suffer from two limitations: 1) They are not good at modeling the relationship between seen and unseen intents. 2) They cannot effectively recognize unseen intents under ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	209,507
2112.08391	Breeding realistic D-brane models	Intersecting branes provide a useful mechanism to construct particle physics models from string theory with a wide variety of desirable characteristics. The landscape of such models can be enormous, and navigating towards regions which are most phenomenologically interesting is potentially challenging. Machine learning...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	271,779
1904.12368	Towards Efficient Model Compression via Learned Global Ranking	Pruning convolutional filters has demonstrated its effectiveness in compressing ConvNets. Prior art in filter pruning requires users to specify a target model complexity (e.g., model size or FLOP count) for the resulting architecture. However, determining a target model complexity can be difficult for optimizing variou...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	129,094
2107.07699	A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers	In recent years, deep learning has made brilliant achievements in Environmental Microorganism (EM) image classification. However, image classification of small EM datasets has still not obtained good research results. Therefore, researchers need to spend a lot of time searching for models with good classification perfo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	246,497
2202.08599	Error Correction for Reliable Quantum Computing	Quantum computers herald the arrival of a new era in which previously intractable computational problems will be solved efficiently. However, quantum technology is held down by decoherence, a phenomenon that is omnipresent in the quantum paradigm and that renders quantum information useless when left unchecked. The sci...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	280,938
2210.07241	Visual Reinforcement Learning with Self-Supervised 3D Representations	A prominent approach to visual Reinforcement Learning (RL) is to learn an internal state representation using self-supervised methods, which has the potential benefit of improved sample-efficiency and generalization through additional learning signal and inductive biases. However, while the real world is inherently 3D,...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	323,630
2501.16029	FDLLM: A Text Fingerprint Detection Method for LLMs in Multi-Language, Multi-Domain Black-Box Environments	Using large language models (LLMs) integration platforms without transparency about which LLM is being invoked can lead to potential security risks. Specifically, attackers may exploit this black-box scenario to deploy malicious models and embed viruses in the code provided to users. In this context, it is increasingly...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	527,796
1811.08853	Resource Mention Extraction for MOOC Discussion Forums	In discussions hosted on discussion forums for MOOCs, references to online learning resources are often of central importance. They contextualize the discussion, anchoring the discussion participants' presentation of the issues and their understanding. However they are usually mentioned in free text, without appropriat...	false	false	false	true	true	true	false	false	true	false	false	false	false	false	false	false	false	true	114,138
2206.04874	The 1st Data Science for Pavements Challenge	The Data Science for Pavement Challenge (DSPC) seeks to accelerate the research and development of automated vision systems for pavement condition monitoring and evaluation by providing a platform with benchmarked datasets and codes for teams to innovate and develop machine learning algorithms that are practice-ready f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	301,807
1707.02880	Deep Bilateral Learning for Real-Time Image Enhancement	Performance is a critical challenge in mobile image processing. Given a reference imaging pipeline, or even human-adjusted pairs of images, we seek to reproduce the enhancements and enable real-time evaluation. For this, we introduce a new neural network architecture inspired by bilateral grid processing and local affi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	76,767
2002.00793	Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach	The connectivity structure of graphs is typically related to the attributes of the nodes. In social networks for example, the probability of a friendship between two people depends on their attributes, such as their age, address, and hobbies. The connectivity of a graph can thus possibly be understood in terms of patte...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,471
2006.07340	Fourier Sparse Leverage Scores and Approximate Kernel Learning	We prove new explicit upper bounds on the leverage scores of Fourier sparse functions under both the Gaussian and Laplace measures. In particular, we study $s$-sparse functions of the form $f(x) = \sum_{j=1}^s a_j e^{i \lambda_j x}$ for coefficients $a_j \in \mathbb{C}$ and frequencies $\lambda_j \in \mathbb{R}$. Bound...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	181,763
2011.07202	Nonuniform Quantized Decoder for Polar Codes with Minimum Distortion Quantizer	We propose a nonuniform quantized decoder for polar codes. The design metric of the quantizers is to minimize the distortion incurred by quantization. The quantizers are obtained via dynamic programming and the optimality of the quantizer is proved as well. Simulation results show that the error correction performance ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	206,471
1608.01783	The Evolutionary Process of Image Transition in Conjunction with Box and Strip Mutation	Evolutionary algorithms have been used in many ways to generate digital art. We study how evolutionary processes are used for evolutionary art and present a new approach to the transition of images. Our main idea is to define evolutionary processes for digital image transition, combining different variants of mutation ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	59,464
2301.08060	Optimal Endurance Race Strategies for a Fully Electric Race Car under Thermal Constraints	This paper presents a bi-level optimization framework to compute the maximum-distance race strategies for a fully electric endurance race car, whilst accounting for the low-level vehicle dynamics and the thermal limitations of the powertrain components. Thereby, the lower level computes the minimum-stint-time for a giv...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	341,083
1910.08412	On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation	Reinforcement learning, mathematically described by Markov Decision Problems, may be approached either through dynamic programming or policy search. Actor-critic algorithms combine the merits of both approaches by alternating between steps to estimate the value function and policy gradient updates. Due to the fact that...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,864
2409.00797	Leveraging parallelizability and channel structure in THz-band, Tbps channel-code decoding	As advancements close the gap between current device capabilities and the requirements for terahertz (THz)-band communications, the demand for terabit-per-second (Tbps) circuits is on the rise. This paper addresses the challenge of achieving Tbps data rates in THz-band communications by focusing on the baseband computa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	485,076
1810.04700	End-to-End Content and Plan Selection for Data-to-Text Generation	Learning to generate fluent natural language from structured data with neural networks has become an common approach for NLG. This problem can be challenging when the form of the structured data varies between examples. This paper presents a survey of several extensions to sequence-to-sequence models to account for the...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	110,089
2408.06382	FedRobo: Federated Learning Driven Autonomous Inter Robots Communication For Optimal Chemical Sprays	Federated Learning enables robots to learn from each other's experiences without relying on centralized data collection. Each robot independently maintains a model of crop conditions and chemical spray effectiveness, which is periodically shared with other robots in the fleet. A communication protocol is designed to op...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	true	480,188
1609.07681	The distribution of information content in English sentences	Sentence is a basic linguistic unit, however, little is known about how information content is distributed across different positions of a sentence. Based on authentic language data of English, the present study calculated the entropy and other entropy-related statistics for different sentence positions. The statistics...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	61,470
2305.14731	AutoDepthNet: High Frame Rate Depth Map Reconstruction using Commodity Depth and RGB Cameras	Depth cameras have found applications in diverse fields, such as computer vision, artificial intelligence, and video gaming. However, the high latency and low frame rate of existing commodity depth cameras impose limitations on their applications. We propose a fast and accurate depth map reconstruction technique to red...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	367,219
2408.14055	HAPM -- Hardware Aware Pruning Method for CNN hardware accelerators in resource constrained devices	During the last years, algorithms known as Convolutional Neural Networks (CNNs) had become increasingly popular, expanding its application range to several areas. In particular, the image processing field has experienced a remarkable advance thanks to this algorithms. In IoT, a wide research field aims to develop hardw...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	483,403
2403.11004	Forward Learning of Graph Neural Networks	Graph neural networks (GNNs) have achieved remarkable success across a wide range of applications, such as recommendation, drug discovery, and question answering. Behind the success of GNNs lies the backpropagation (BP) algorithm, which is the de facto standard for training deep neural networks (NNs). However, despite ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	438,476
1903.05543	Adversarial attacks against Fact Extraction and VERification	This paper describes a baseline for the second iteration of the Fact Extraction and VERification shared task (FEVER2.0) which explores the resilience of systems through adversarial evaluation. We present a collection of simple adversarial attacks against systems that participated in the first FEVER shared task. FEVER m...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	124,185
2309.00398	VideoGen: A Reference-Guided Latent Diffusion Approach for High Definition Text-to-Video Generation	In this paper, we present VideoGen, a text-to-video generation approach, which can generate a high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion. We leverage an off-the-shelf text-to-image generation model, e.g., Stable Diffusion, to generate an image ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	389,300
1906.09610	Improving Description-based Person Re-identification by Multi-granularity Image-text Alignments	Description-based person re-identification (Re-id) is an important task in video surveillance that requires discriminative cross-modal representations to distinguish different people. It is difficult to directly measure the similarity between images and descriptions due to the modality heterogeneity (the cross-modal pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	136,217
1705.02494	Learning Distributed Representations of Texts and Entities from Knowledge Base	We describe a neural network model that jointly learns distributed representations of texts and knowledge base (KB) entities. Given a text in the KB, we train our proposed model to predict entities that are relevant to the text. Our model is designed to be generic with the ability to address various NLP tasks with ease...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	73,005
2406.19640	Efficient Event Stream Super-Resolution with Recursive Multi-Branch Fusion	Current Event Stream Super-Resolution (ESR) methods overlook the redundant and complementary information present in positive and negative events within the event stream, employing a direct mixing approach for super-resolution, which may lead to detail loss and inefficiency. To address these issues, we propose an effici...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	468,502
1710.10182	High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks	Synthesizing face sketches from real photos and its inverse have many applications. However, photo/sketch synthesis remains a challenging problem due to the fact that photo and sketch have different characteristics. In this work, we consider this task as an image-to-image translation problem and explore the recently po...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	83,324
2502.14172	Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation	In this paper, we investigate the finite-sample statistical rates of distributional temporal difference (TD) learning with linear function approximation. The aim of distributional TD learning is to estimate the return distribution of a discounted Markov decision process for a given policy {\pi}. Prior works on statisti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	535,696
2203.11754	Exploring and Evaluating Image Restoration Potential in Dynamic Scenes	In dynamic scenes, images often suffer from dynamic blur due to superposition of motions or low signal-noise ratio resulted from quick shutter speed when avoiding motions. Recovering sharp and clean results from the captured images heavily depends on the ability of restoration methods and the quality of the input. Alth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,029
2305.18353	Emergent representations in networks trained with the Forward-Forward algorithm	The Backpropagation algorithm has often been criticised for its lack of biological realism. In an attempt to find a more biologically plausible alternative, the recently introduced Forward-Forward algorithm replaces the forward and backward passes of Backpropagation with two forward passes. In this work, we show that t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	368,977
1605.08323	Aerial image geolocalization from recognition and matching of roads and intersections	Aerial image analysis at a semantic level is important in many applications with strong potential impact in industry and consumer use, such as automated mapping, urban planning, real estate and environment monitoring, or disaster relief. The problem is enjoying a great interest in computer vision and remote sensing, du...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	56,416
1802.03209	Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success Rule	This paper explores the use of the standard approach for proving runtime bounds in discrete domains---often referred to as drift analysis---in the context of optimization on a continuous domain. Using this framework we analyze the (1+1) Evolution Strategy with one-fifth success rule on the sphere function. To deal with...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	89,921
2403.16137	A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective	Graph self-supervised learning (SSL) is now a go-to method for pre-training graph foundation models (GFMs). There is a wide variety of knowledge patterns embedded in the graph data, such as node properties and clusters, which are crucial to learning generalized representations for GFMs. However, existing surveys of GFM...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	440,891
2008.06232	Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs	Open Government Data (OGD) is being published by various public administration organizations around the globe. Within the metadata of OGD data catalogs, the publishing organizations (1) are not uniquely and unambiguously identifiable and, even worse, (2) change over time, by public administration units being merged or ...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	191,741
2006.05927	Recent Advances in 3D Object and Hand Pose Estimation	3D object and hand pose estimation have huge potentials for Augmented Reality, to enable tangible interfaces, natural interfaces, and blurring the boundaries between the real and virtual worlds. In this chapter, we present the recent developments for 3D object and hand pose estimation using cameras, and discuss their a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	181,251
2401.06000	Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer Interaction: A Comprehensive Survey	Due to the fact that roughly sixty percent of the human body is essentially composed of water, the human body is inherently a conductive object, being able to, firstly, form an inherent electric field from the body to the surroundings and secondly, deform the distribution of an existing electric field near the body. Bo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	420,985
1907.11542	Towards the Enhancement of Body Standing Balance Recovery by Means of a Wireless Audio-Biofeedback System	Human maintain their body balance by sensorimotor controls mainly based on information gathered from vision, proprioception and vestibular systems. When there is a lack of information, caused by pathologies, diseases or aging, the subject may fall. In this context, we developed a system to augment information gathering...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	139,876
1811.12143	Learning to Reason with Third-Order Tensor Products	We combine Recurrent Neural Networks with Tensor Product Representations to learn combinatorial representations of sequential data. This improves symbolic interpretation and systematic generalisation. Our architecture is trained end-to-end through gradient descent on a variety of simple natural language reasoning tasks...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	114,941
0812.4334	Multi-User SISO Precoding based on Generalized Multi-Unitary Decomposition for Single-carrier Transmission in Frequency Selective Channel	In this paper, we propose to exploit the richly scattered multi-path nature of a frequency selective channel to provide additional degrees of freedom for desigining effective precoding schemes for multi-user communications. We design the precoding matrix for multi-user communications based on the Generalized Multi-Unit...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,839
1805.09025	Joint String Complexity for Markov Sources: Small Data Matters	String complexity is defined as the cardinality of a set of all distinct words (factors) of a given string. For two strings, we introduce the joint string complexity as the cardinality of a set of words that are common to both strings. String complexity finds a number of applications from capturing the richness of a la...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	98,322
2108.11608	Improving HRI through robot architecture transparency	In recent years, an increased effort has been invested to improve the capabilities of robots. Nevertheless, human-robot interaction remains a complex field of application where errors occur frequently. The reasons for these errors can primarily be divided into two classes. Foremost, the recent increase in capabilities ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	252,227
2208.12813	Abnormal Local Clustering in Federated Learning	Federated learning is a model for privacy without revealing private data by transfer models instead of personal and private data from local client devices. While, in the global model, it's crucial to recognize each local data is normal. This paper suggests one method to separate normal locals and abnormal locals by Euc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	314,860
2210.06722	Few-shot Relational Reasoning via Connection Subgraph Pretraining	Few-shot knowledge graph (KG) completion task aims to perform inductive reasoning over the KG: given only a few support triplets of a new relation $\bowtie$ (e.g., (chop,$\bowtie$,kitchen), (read,$\bowtie$,library), the goal is to predict the query triplets of the same unseen relation $\bowtie$, e.g., (sleep,$\bowtie$,...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	323,413
2308.10304	Economic Policy Uncertainty: A Review on Applications and Measurement Methods with Focus on Text Mining Methods	Economic Policy Uncertainty (EPU) represents the uncertainty realized by the investors during economic policy alterations. EPU is a critical indicator in economic studies to predict future investments, the unemployment rate, and recessions. EPU values can be estimated based on financial parameters directly or implied u...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	386,667
2005.02523	Partly Supervised Multitask Learning	Semi-supervised learning has recently been attracting attention as an alternative to fully supervised models that require large pools of labeled data. Moreover, optimizing a model for multiple tasks can provide better generalizability than single-task learning. Leveraging self-supervision and adversarial training, we p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	175,893
2106.03050	Efficient Continuous Control with Double Actors and Regularized Critics	How to obtain good value estimation is one of the key problems in Reinforcement Learning (RL). Current value estimation methods, such as DDPG and TD3, suffer from unnecessary over- or underestimation bias. In this paper, we explore the potential of double actors, which has been neglected for a long time, for better val...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	239,151
2502.04740	SelaFD:Seamless Adaptation of Vision Transformer Fine-tuning for Radar-based Human Activity	Human Activity Recognition (HAR) such as fall detection has become increasingly critical due to the aging population, necessitating effective monitoring systems to prevent serious injuries and fatalities associated with falls. This study focuses on fine-tuning the Vision Transformer (ViT) model specifically for HAR usi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	531,299
2412.19812	Pharmacophore-guided de novo drug design with diffusion bridge	De novo design of bioactive drug molecules with potential to treat desired biological targets is a profound task in the drug discovery process. Existing approaches tend to leverage the pocket structure of the target protein to condition the molecule generation. However, even the pocket area of the target protein may co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	520,975
2209.13716	Hamiltonian Adaptive Importance Sampling	Importance sampling (IS) is a powerful Monte Carlo (MC) methodology for approximating integrals, for instance in the context of Bayesian inference. In IS, the samples are simulated from the so-called proposal distribution, and the choice of this proposal is key for achieving a high performance. In adaptive IS (AIS) met...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	319,999
2310.01413	A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network	Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the wealth of radiology imaging data collected through standard care, however, has significantly lagged other domains. Such data is ripe for us...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	396,411
0806.2943	Modern Set	In this paper, we intend to generalize the classical set theory as much as possible. we will do this by freeing sets from the regular properties of classical sets; e.g., the law of excluded middle, the law of non-contradiction, the distributive law, the commutative law,etc....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,936
2411.01123	X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios	Recent advancements have exploited diffusion models for the synthesis of either LiDAR point clouds or camera image data in driving scenarios. Despite their success in modeling single-modality data marginal distribution, there is an under-exploration in the mutual reliance between different modalities to describe comple...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	504,921
1612.04130	Cramer-Rao Lower Bound for DoA Estimation with RF Lens-Embedded Antenna Array	In this paper, we consider the Cramer-Rao lower bound (CRLB) for estimation of a lens-embedded antenna array with deterministic parameters. Unlike CRLB of uniform linear array (ULA), it is noted that CRLB for direction of arrival (DoA) of lens-embedded antenna array is dominated by not only angle but characteristics of...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	65,486
2003.03433	Reward Design in Cooperative Multi-agent Reinforcement Learning for Packet Routing	In cooperative multi-agent reinforcement learning (MARL), how to design a suitable reward signal to accelerate learning and stabilize convergence is a critical problem. The global reward signal assigns the same global reward to all agents without distinguishing their contributions, while the local reward signal provide...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	167,212
2207.02134	Balancing Profit, Risk, and Sustainability for Portfolio Management	Stock portfolio optimization is the process of continuous reallocation of funds to a selection of stocks. This is a particularly well-suited problem for reinforcement learning, as daily rewards are compounding and objective functions may include more than just profit, e.g., risk and sustainability. We developed a novel...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	306,414
1909.01940	Can we trust deep learning models diagnosis? The impact of domain shift in chest radiograph classification	While deep learning models become more widespread, their ability to handle unseen data and generalize for any scenario is yet to be challenged. In medical imaging, there is a high heterogeneity of distributions among images based on the equipment that generates them and their parametrization. This heterogeneity trigger...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	144,052
1804.03541	Sensing Hidden Vehicles by Exploiting Multi-Path V2V Transmission	This paper presents a technology of sensing hidden vehicles by exploiting multi-path vehicle-to-vehicle (V2V) communication. This overcomes the limitation of existing RADAR technologies that requires line-of-sight (LoS), thereby enabling more intelligent manoeuvre in autonomous driving and improving its safety. The pro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	94,649
0904.3165	Fading Broadcast Channels with State Information at the Receivers	Despite considerable progress on the information-theoretic broadcast channel, the capacity region of fading broadcast channels with channel state known at the receivers but unknown at the transmitter remains unresolved. We address this subject by introducing a layered erasure broadcast channel model in which each compo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,566
2209.00820	Structural Bias for Aspect Sentiment Triplet Extraction	Structural bias has recently been exploited for aspect sentiment triplet extraction (ASTE) and led to improved performance. On the other hand, it is recognized that explicitly incorporating structural bias would have a negative impact on efficiency, whereas pretrained language models (PLMs) can already capture implicit...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	315,693
2406.12316	Enhancing Visible-Infrared Person Re-identification with Modality- and Instance-aware Visual Prompt Learning	The Visible-Infrared Person Re-identification (VI ReID) aims to match visible and infrared images of the same pedestrians across non-overlapped camera views. These two input modalities contain both invariant information, such as shape, and modality-specific details, such as color. An ideal model should utilize valuable...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	465,340
2207.03524	Aerobatic Trajectory Generation for a VTOL Fixed-Wing Aircraft Using Differential Flatness	This paper proposes a novel algorithm for aerobatic trajectory generation for a vertical take-off and landing (VTOL) tailsitter flying wing aircraft. The algorithm differs from existing approaches for fixed-wing trajectory generation, as it considers a realistic six-degree-of-freedom (6DOF) flight dynamics model, inclu...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	306,872
2203.03157	SingleSketch2Mesh : Generating 3D Mesh model from Sketch	Sketching is an important activity in any design process. Designers and stakeholders share their ideas through hand-drawn sketches. These sketches are further used to create 3D models. Current methods to generate 3D models from sketches are either manual or tightly coupled with 3D modeling platforms. Therefore, it requ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,992
2109.04654	Per Garment Capture and Synthesis for Real-time Virtual Try-on	Virtual try-on is a promising application of computer graphics and human computer interaction that can have a profound real-world impact especially during this pandemic. Existing image-based works try to synthesize a try-on image from a single image of a target garment, but it inherently limits the ability to react to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	254,484
2009.06764	Private data sharing between decentralized users through the privGAN architecture	More data is almost always beneficial for analysis and machine learning tasks. In many realistic situations however, an enterprise cannot share its data, either to keep a competitive advantage or to protect the privacy of the data sources, the enterprise's clients for example. We propose a method for data owners to sha...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	195,735
2008.11364	Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models	Federated learning (FL) is a promising way to use the computing power of mobile devices while maintaining the privacy of users. Current work in FL, however, makes the unrealistic assumption that the users have ground-truth labels on their devices, while also assuming that the server has neither data nor labels. In this...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,256
2306.01506	BabySLM: language-acquisition-friendly benchmark of self-supervised spoken language models	Self-supervised techniques for learning speech representations have been shown to develop linguistic competence from exposure to speech without the need for human labels. In order to fully realize the potential of these approaches and further our understanding of how infants learn language, simulations must closely emu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	370,489
2203.10131	Half-Inverse Gradients for Physical Deep Learning	Recent works in deep learning have shown that integrating differentiable physics simulators into the training process can greatly improve the quality of results. Although this combination represents a more complex optimization task than supervised neural network training, the same gradient-based optimizers are typicall...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	286,409
2001.06962	On the Joint Typicality of Permutations of Sequences of Random Variables	Permutations of correlated sequences of random variables appear naturally in a variety of applications such as graph matching and asynchronous communications. In this paper, the asymptotic statistical behavior of such permuted sequences is studied. It is assumed that a collection of random vectors is produced based on ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	160,939
2005.02627	Joint Optimal Software Caching, Computation Offloading and Communications Resource Allocation for Mobile Edge Computing	As software may be used by multiple users, caching popular software at the wireless edge has been considered to save computation and communications resources for mobile edge computing (MEC). However, fetching uncached software from the core network and multicasting popular software to users have so far been ignored. Th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	175,933
2310.02420	FedL2P: Federated Learning to Personalize	Federated learning (FL) research has made progress in developing algorithms for distributed learning of global models, as well as algorithms for local personalization of those common models to the specifics of each client's local data distribution. However, different FL problems may require different personalization st...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	396,837
1308.0777	A testing based extraction algorithm for identifying significant communities in networks	A common and important problem arising in the study of networks is how to divide the vertices of a given network into one or more groups, called communities, in such a way that vertices of the same community are more interconnected than vertices belonging to different ones. We propose and investigate a testing based co...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	26,253
1312.3092	A Low-Complexity Detector for Memoryless Polarization-Multiplexed Fiber-Optical Channels	A low-complexity detector is introduced for polarization-multiplexed M-ary phase shift keying modulation in a fiber-optical channel impaired by nonlinear phase noise, generalizing a previous result by Lau and Kahn for single-polarization signals. The proposed detector uses phase compensation based on both received sign...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	29,016
2212.05909	NFResNet: Multi-scale and U-shaped Networks for Deblurring	Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast F...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	335,933
2408.03336	Few-Shot Transfer Learning for Individualized Braking Intent Detection on Neuromorphic Hardware	Objective: This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a BrainChip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used group-level, models using electroencephalographic data. Ma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	478,974
1802.00752	Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis	Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists. Computer-aided diagnosis systems showed potential for improving the diagnostic a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,465
2112.04827	Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models	It is challenging to derive explainability for unsupervised or statistical-based face image quality assessment (FIQA) methods. In this work, we propose a novel set of explainability tools to derive reasoning for different FIQA decisions and their face recognition (FR) performance implications. We avoid limiting the dep...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	270,656
2409.04639	High-Speed and Impact Resilient Teleoperation of Humanoid Robots	Teleoperation of humanoid robots has long been a challenging domain, necessitating advances in both hardware and software to achieve seamless and intuitive control. This paper presents an integrated solution based on several elements: calibration-free motion capture and retargeting, low-latency fast whole-body kinemati...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	486,453
2211.13778	Design and Prototyping Distributed CNN Inference Acceleration in Edge Computing	For time-critical IoT applications using deep learning, inference acceleration through distributed computing is a promising approach to meet a stringent deadline. In this paper, we implement a working prototype of a new distributed inference acceleration method HALP using three raspberry Pi 4. HALP accelerates inferenc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	332,591
2103.04537	Multimodal Representation Learning via Maximization of Local Mutual Information	We propose and demonstrate a representation learning approach by maximizing the mutual information between local features of images and text. The goal of this approach is to learn useful image representations by taking advantage of the rich information contained in the free text that describes the findings in the image...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	223,673
1310.2547	All Your Location are Belong to Us: Breaking Mobile Social Networks for Automated User Location Tracking	Many popular location-based social networks (LBSNs) support built-in location-based social discovery with hundreds of millions of users around the world. While user (near) realtime geographical information is essential to enable location-based social discovery in LBSNs, the importance of user location privacy has also ...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	27,684
2103.08802	Parareal Neural Networks Emulating a Parallel-in-time Algorithm	As deep neural networks (DNNs) become deeper, the training time increases. In this perspective, multi-GPU parallel computing has become a key tool in accelerating the training of DNNs. In this paper, we introduce a novel methodology to construct a parallel neural network that can utilize multiple GPUs simultaneously fr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	224,989
2412.14435	Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine	The importance of time series forecasting drives continuous research and the development of new approaches to tackle this problem. Typically, these methods are introduced through empirical studies that frequently claim superior accuracy for the proposed approaches. Nevertheless, concerns are rising about the reliabilit...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	518,695
2309.02722	Reinforcement Learning of Action and Query Policies with LTL Instructions under Uncertain Event Detector	Reinforcement learning (RL) with linear temporal logic (LTL) objectives can allow robots to carry out symbolic event plans in unknown environments. Most existing methods assume that the event detector can accurately map environmental states to symbolic events; however, uncertainty is inevitable for real-world event det...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	390,144
2111.12790	Temporal Effects on Pre-trained Models for Language Processing Tasks	Keeping the performance of language technologies optimal as time passes is of great practical interest. We study temporal effects on model performance on downstream language tasks, establishing a nuanced terminology for such discussion and identifying factors essential to conduct a robust study. We present experiments ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	268,070
2210.07111	A Multi-dimensional Evaluation of Tokenizer-free Multilingual Pretrained Models	Recent work on tokenizer-free multilingual pretrained models show promising results in improving cross-lingual transfer and reducing engineering overhead (Clark et al., 2022; Xue et al., 2022). However, these works mainly focus on reporting accuracy on a limited set of tasks and data settings, placing less emphasis on ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	323,577
2406.03299	The Good, the Bad, and the Hulk-like GPT: Analyzing Emotional Decisions of Large Language Models in Cooperation and Bargaining Games	Behavior study experiments are an important part of society modeling and understanding human interactions. In practice, many behavioral experiments encounter challenges related to internal and external validity, reproducibility, and social bias due to the complexity of social interactions and cooperation in human user ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	461,187
2209.11896	Unsupervised active speaker detection in media content using cross-modal information	We present a cross-modal unsupervised framework for active speaker detection in media content such as TV shows and movies. Machine learning advances have enabled impressive performance in identifying individuals from speech and facial images. We leverage speaker identity information from speech and faces, and formulate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	319,340
2010.12632	Biologically plausible single-layer networks for nonnegative independent component analysis	An important problem in neuroscience is to understand how brains extract relevant signals from mixtures of unknown sources, i.e., perform blind source separation. To model how the brain performs this task, we seek a biologically plausible single-layer neural network implementation of a blind source separation algorithm...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	202,767
2403.06793	Boosting Image Restoration via Priors from Pre-trained Models	Pre-trained models with large-scale training data, such as CLIP and Stable Diffusion, have demonstrated remarkable performance in various high-level computer vision tasks such as image understanding and generation from language descriptions. Yet, their potential for low-level tasks such as image restoration remains rel...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,604
2205.07857	Neural Program Synthesis with Query	Aiming to find a program satisfying the user intent given input-output examples, program synthesis has attracted increasing interest in the area of machine learning. Despite the promising performance of existing methods, most of their success comes from the privileged information of well-designed input-output examples....	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	296,736
2303.16898	Bagging by Learning to Singulate Layers Using Interactive Perception	Many fabric handling and 2D deformable material tasks in homes and industry require singulating layers of material such as opening a bag or arranging garments for sewing. In contrast to methods requiring specialized sensing or end effectors, we use only visual observations with ordinary parallel jaw grippers. We propos...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	355,033
2302.04840	What are the mechanisms underlying metacognitive learning?	How is it that humans can solve complex planning tasks so efficiently despite limited cognitive resources? One reason is its ability to know how to use its limited computational resources to make clever choices. We postulate that people learn this ability from trial and error (metacognitive reinforcement learning). Her...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	344,838
2410.15222	AutoFLUKA: A Large Language Model Based Framework for Automating Monte Carlo Simulations in FLUKA	Monte Carlo (MC) simulations, particularly using FLUKA, are essential for replicating real-world scenarios across scientific and engineering fields. Despite the robustness and versatility, FLUKA faces significant limitations in automation and integration with external post-processing tools, leading to workflows with a ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	500,425
2412.03400	Implicit Priors Editing in Stable Diffusion via Targeted Token Adjustment	Implicit assumptions and priors are often necessary in text-to-image generation tasks, especially when textual prompts lack sufficient context. However, these assumptions can sometimes reflect outdated concepts, inaccuracies, or societal bias embedded in the training data. We present Embedding-only Editing (Embedit), a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,945
2407.05244	Some Issues in Predictive Ethics Modeling: An Annotated Contrast Set of "Moral Stories"	Models like Delphi have been able to label ethical dilemmas as moral or immoral with astonishing accuracy. This paper challenges accuracy as a holistic metric for ethics modeling by identifying issues with translating moral dilemmas into text-based input. It demonstrates these issues with contrast sets that substantial...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	470,884

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