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
2403.17881	Deepfake Generation and Detection: A Benchmark and Survey	Deepfake is a technology dedicated to creating highly realistic facial images and videos under specific conditions, which has significant application potential in fields such as entertainment, movie production, digital human creation, to name a few. With the advancements in deep learning, techniques primarily represent...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	441,672
1008.4370	Fourier Domain Decoding Algorithm of Non-Binary LDPC codes for Parallel Implementation	For decoding non-binary low-density parity check (LDPC) codes, logarithm-domain sum-product (Log-SP) algorithms were proposed for reducing quantization effects of SP algorithm in conjunction with FFT. Since FFT is not applicable in the logarithm domain, the computations required at check nodes in the Log-SP algorithms ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	7,376
1806.04497	A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation	Accidents and attacks that involve chemical, biological, radiological/nuclear or explosive (CBRNE) substances are rare, but can be of high consequence. Since the investigation of such events is not anybody's routine work, a range of AI techniques can reduce investigators' cognitive load and support decision-making, inc...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	100,246
2407.12013	Dating ancient manuscripts using radiocarbon and AI-based writing style analysis	Determining the chronology of ancient handwritten manuscripts is essential for reconstructing the evolution of ideas. For the Dead Sea Scrolls, this is particularly important. However, there is an almost complete lack of date-bearing manuscripts evenly distributed across the timeline and written in similar scripts avai...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	true	473,721
2207.12884	CFLIT: Coexisting Federated Learning and Information Transfer	Future wireless networks are expected to support diverse mobile services, including artificial intelligence (AI) services and ubiquitous data transmissions. Federated learning (FL), as a revolutionary learning approach, enables collaborative AI model training across distributed mobile edge devices. By exploiting the su...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	310,147
2312.11299	Uncertainty-based Fairness Measures	Unfair predictions of machine learning (ML) models impede their broad acceptance in real-world settings. Tackling this arduous challenge first necessitates defining what it means for an ML model to be fair. This has been addressed by the ML community with various measures of fairness that depend on the prediction outco...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	416,507
2202.00791	Mars Terrain Segmentation with Less Labels	Planetary rover systems need to perform terrain segmentation to identify drivable areas as well as identify specific types of soil for sample collection. The latest Martian terrain segmentation methods rely on supervised learning which is very data hungry and difficult to train where only a small number of labeled samp...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	278,258
2211.13032	Monte Carlo Tree Search Algorithms for Risk-Aware and Multi-Objective Reinforcement Learning	In many risk-aware and multi-objective reinforcement learning settings, the utility of the user is derived from a single execution of a policy. In these settings, making decisions based on the average future returns is not suitable. For example, in a medical setting a patient may only have one opportunity to treat thei...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	332,329
1004.2003	The Socceral Force	We have an audacious dream, we would like to develop a simulation and virtual reality system to support the decision making in European football (soccer). In this review, we summarize the efforts that we have made to fulfil this dream until recently. In addition, an introductory version of FerSML (Footballer and Footba...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	6,148
2406.18359	Optimizing Extension Techniques for Discovering Non-Algebraic Matroids	In this work, we revisit some combinatorial and information-theoretic extension techniques for detecting non-algebraic matroids. These are the Dress-Lov\'asz and Ahlswede-K\"orner extension properties. We provide optimizations of these techniques to reduce their computational complexity, finding new non-algebraic matro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	467,980
1802.01527	Supporting UAV Cellular Communications through Massive MIMO	In this article, we provide a much-needed study of UAV cellular communications, focusing on the rates achievable for the UAV downlink command and control (C&C) channel. For this key performance indicator, we perform a realistic comparison between existing deployments operating in single-user mode and next-generation mu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	89,625
1605.00529	Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning	Faced with massive data, is it possible to trade off (statistical) risk, and (computational) space and time? This challenge lies at the heart of large-scale machine learning. Using k-means clustering as a prototypical unsupervised learning problem, we show how we can strategically summarize the data (control space) in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	55,358
1510.07163	Evolutionary Landscape and Management of Population Diversity	The search ability of an Evolutionary Algorithm (EA) depends on the variation among the individuals in the population [3, 4, 8]. Maintaining an optimal level of diversity in the EA population is imperative to ensure that progress of the EA search is unhindered by premature convergence to suboptimal solutions. Clearer u...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	48,173
2402.09486	UMOEA/D: A Multiobjective Evolutionary Algorithm for Uniform Pareto Objectives based on Decomposition	Multiobjective optimization (MOO) is prevalent in numerous applications, in which a Pareto front (PF) is constructed to display optima under various preferences. Previous methods commonly utilize the set of Pareto objectives (particles on the PF) to represent the entire PF. However, the empirical distribution of the Pa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,548
2401.08668	Thermodynamic Perspectives on Computational Complexity: Exploring the P vs. NP Problem	The resolution of the P vs. NP problem, a cornerstone in computational theory, remains elusive despite extensive exploration through mathematical logic and algorithmic theory. This paper takes a novel approach by integrating information theory, thermodynamics, and computational complexity, offering a comprehensive land...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	421,982
2211.00151	A Close Look into the Calibration of Pre-trained Language Models	Pre-trained language models (PLMs) may fail in giving reliable estimates of their predictive uncertainty. We take a close look into this problem, aiming to answer two questions: (1) Do PLMs learn to become calibrated in the training process? (2) How effective are existing calibration methods? For the first question, we...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	327,769
2411.02738	Novelty-focused R&D landscaping using transformer and local outlier factor	While numerous studies have explored the field of research and development (R&D) landscaping, the preponderance of these investigations has emphasized predictive analysis based on R&D outcomes, specifically patents, and academic literature. However, the value of research proposals and novelty analysis has seldom been a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	505,637
2501.02362	Easing Optimization Paths: a Circuit Perspective	Gradient descent is the method of choice for training large artificial intelligence systems. As these systems become larger, a better understanding of the mechanisms behind gradient training would allow us to alleviate compute costs and help steer these systems away from harmful behaviors. To that end, we suggest utili...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	522,453
2108.04476	SP-GAN: Sphere-Guided 3D Shape Generation and Manipulation	We present SP-GAN, a new unsupervised sphere-guided generative model for direct synthesis of 3D shapes in the form of point clouds. Compared with existing models, SP-GAN is able to synthesize diverse and high-quality shapes with fine details and promote controllability for part-aware shape generation and manipulation, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	250,016
2008.03201	Convolutional neural network based deep-learning architecture for intraprostatic tumour contouring on PSMA PET images in patients with primary prostate cancer	Accurate delineation of the intraprostatic gross tumour volume (GTV) is a prerequisite for treatment approaches in patients with primary prostate cancer (PCa). Prostate-specific membrane antigen positron emission tomography (PSMA-PET) may outperform MRI in GTV detection. However, visual GTV delineation underlies intero...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	190,832
2410.13964	Enhancing Generalization in Sparse Mixture of Experts Models: The Case for Increased Expert Activation in Compositional Tasks	As Transformer models grow in complexity, their ability to generalize to novel, compositional tasks becomes crucial. This study challenges conventional wisdom about sparse activation in Sparse Mixture of Experts (SMoE) models when faced with increasingly complex compositional tasks. Through experiments on the SRAVEN sy...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	499,796
2006.05238	An Efficient Accelerator Design Methodology for Deformable Convolutional Networks	Deformable convolutional networks have demonstrated outstanding performance in object recognition tasks with an effective feature extraction. Unlike standard convolution, the deformable convolution decides the receptive field size using dynamically generated offsets, which leads to an irregular memory access. Especiall...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	180,991
2305.10427	Accelerating Transformer Inference for Translation via Parallel Decoding	Autoregressive decoding limits the efficiency of transformers for Machine Translation (MT). The community proposed specific network architectures and learning-based methods to solve this issue, which are expensive and require changes to the MT model, trading inference speed at the cost of the translation quality. In th...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	365,054
1610.07328	SSH (Sketch, Shingle, & Hash) for Indexing Massive-Scale Time Series	Similarity search on time series is a frequent operation in large-scale data-driven applications. Sophisticated similarity measures are standard for time series matching, as they are usually misaligned. Dynamic Time Warping or DTW is the most widely used similarity measure for time series because it combines alignment ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	62,772
2302.12517	Knock Out 2PC with Practicality Intact: a High-performance and General Distributed Transaction Protocol (Technical Report)	Two-phase-commit (2PC) has been widely adopted for distributed transaction processing, but it also jeopardizes throughput by introducing two rounds of network communications and two durable log writes to a transaction's critical path. Despite the various proposals that eliminate 2PC such as deterministic database and a...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	347,600
2004.12765	ColBERT: Using BERT Sentence Embedding in Parallel Neural Networks for Computational Humor	Automation of humor detection and rating has interesting use cases in modern technologies, such as humanoid robots, chatbots, and virtual assistants. In this paper, we propose a novel approach for detecting and rating humor in short texts based on a popular linguistic theory of humor. The proposed technical method init...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	174,345
2203.06210	Leveraging universality of jet taggers through transfer learning	A significant challenge in the tagging of boosted objects via machine-learning technology is the prohibitive computational cost associated with training sophisticated models. Nevertheless, the universality of QCD suggests that a large amount of the information learnt in the training is common to different physical sign...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	285,033
2404.08469	Supervisory Control Theory with Event Forcing	In the Ramadge-Wonham supervisory control theory the only interaction mechanism between supervisor and plant is that the supervisor may enable/disable events from the plant and the plant makes a final decision about which of the enabled events is actually taking place. In this paper, the interaction between supervisor ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	446,253
0807.3094	Energy-Efficient Resource Allocation in Multiuser MIMO Systems: A Game-Theoretic Framework	This paper focuses on the cross-layer issue of resource allocation for energy efficiency in the uplink of a multiuser MIMO wireless communication system. Assuming that all of the transmitters and the uplink receiver are equipped with multiple antennas, the situation considered is that in which each terminal is allowed ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	2,088
2204.12634	Discrete-Time Adaptive Control of a Class of Nonlinear Systems Using High-Order Tuners	This paper concerns the adaptive control of a class of discrete-time nonlinear systems with all states accessible. Recently, a high-order tuner algorithm was developed for the minimization of convex loss functions with time-varying regressors in the context of an identification problem. Based on Nesterov's algorithm, t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	293,541
2011.11985	Adam$^+$: A Stochastic Method with Adaptive Variance Reduction	Adam is a widely used stochastic optimization method for deep learning applications. While practitioners prefer Adam because it requires less parameter tuning, its use is problematic from a theoretical point of view since it may not converge. Variants of Adam have been proposed with provable convergence guarantee, but ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	208,020
2005.08424	Single-sample writers -- "Document Filter" and their impacts on writer identification	The writing can be used as an important biometric modality which allows to unequivocally identify an individual. It happens because the writing of two different persons present differences that can be explored both in terms of graphometric properties or even by addressing the manuscript as a digital image, taking into ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	177,613
2010.00796	JAKET: Joint Pre-training of Knowledge Graph and Language Understanding	Knowledge graphs (KGs) contain rich information about world knowledge, entities and relations. Thus, they can be great supplements to existing pre-trained language models. However, it remains a challenge to efficiently integrate information from KG into language modeling. And the understanding of a knowledge graph requ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	198,396
2401.14285	POUR-Net: A Population-Prior-Aided Over-Under-Representation Network for Low-Count PET Attenuation Map Generation	Low-dose PET offers a valuable means of minimizing radiation exposure in PET imaging. However, the prevalent practice of employing additional CT scans for generating attenuation maps (u-map) for PET attenuation correction significantly elevates radiation doses. To address this concern and further mitigate radiation exp...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	424,036
1904.12533	A Complete Classification of the Complexity and Rewritability of Ontology-Mediated Queries based on the Description Logic EL	We provide an ultimately fine-grained analysis of the data complexity and rewritability of ontology-mediated queries (OMQs) based on an EL ontology and a conjunctive query (CQ). Our main results are that every such OMQ is in AC0, NL-complete, or PTime-complete and that containment in NL coincides with rewritability int...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	129,125
2405.14347	Doubly-Dynamic ISAC Precoding for Vehicular Networks: A Constrained Deep Reinforcement Learning (CDRL) Approach	Integrated sensing and communication (ISAC) technology is essential for supporting vehicular networks. However, the communication channel in this scenario exhibits time variations, and the potential targets may move rapidly, resulting in double dynamics. This nature poses a challenge for real-time precoder design. Whil...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	456,380
1611.05995	Wireless-powered relaying with finite block-length codes	This paper studies the outage probability and the throughput of amplify-and-forward relay networks with wireless information and energy transfer. We use some recent results on finite block-length codes to analyze the system performance in the cases with short codewords. Specifically, the time switching relaying and the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	64,109
2305.13040	SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents	Task-oriented dialogue (TOD) models have made significant progress in recent years. However, previous studies primarily focus on datasets written by annotators, which has resulted in a gap between academic research and real-world spoken conversation scenarios. While several small-scale spoken TOD datasets are proposed ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	366,310
1505.07427	PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization	We present a robust and real-time monocular six degree of freedom relocalization system. Our system trains a convolutional neural network to regress the 6-DOF camera pose from a single RGB image in an end-to-end manner with no need of additional engineering or graph optimisation. The algorithm can operate indoors and o...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	43,541
2303.07810	Disentangled Graph Social Recommendation	Social recommender systems have drawn a lot of attention in many online web services, because of the incorporation of social information between users in improving recommendation results. Despite the significant progress made by existing solutions, we argue that current methods fall short in two limitations: (1) Existi...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	351,389
2312.04511	An LLM Compiler for Parallel Function Calling	The reasoning capabilities of the recent LLMs enable them to execute external function calls to overcome their inherent limitations, such as knowledge cutoffs, poor arithmetic skills, or lack of access to private data. This development has allowed LLMs to select and coordinate multiple functions based on the context to...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	413,698
1807.04801	Practical Obstacles to Deploying Active Learning	Active learning (AL) is a widely-used training strategy for maximizing predictive performance subject to a fixed annotation budget. In AL one iteratively selects training examples for annotation, often those for which the current model is most uncertain (by some measure). The hope is that active sampling leads to bette...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	102,792
1305.2713	Early Detection of Alzheimer's - A Crucial Requirement	Alzheimer's, an old age disease of people over 65 years causes problems with memory, thinking and behavior. This disease progresses very slow and its identification in early stages is very difficult. The symptoms of Alzheimer's appear slowly and gradually will have worse effects. In its early stages, not only the patie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	24,540
2110.13681	Malicious Mode Attack on EV Coordinated Charging Load and MIADRC Defense Strategy	The Internet of Things (IoT) provides a salient communication environment to facilitate the coordinated charging of electric vehicle (EV) load. However, as IoT is connected with the public network, the coordinated charging system is in a low-level cyber security and greatly vulnerable to malicious attacks. This paper i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	263,280
1804.02032	A Multi-Layer Approach to Superpixel-based Higher-order Conditional Random Field for Semantic Image Segmentation	Superpixel-based Higher-order Conditional random fields (SP-HO-CRFs) are known for their effectiveness in enforcing both short and long spatial contiguity for pixelwise labelling in computer vision. However, their higher-order potentials are usually too complex to learn and often incur a high computational cost in perf...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,325
2008.10323	Experimental Verification of Stability Theory for a Planar Rigid Body with Two Unilateral Frictional Contacts	Stability of equilibrium states in mechanical systems with multiple unilateral frictional contacts is an important practical requirement, with high relevance for robotic applications. In our previous work, we theoretically analyzed finite-time Lyapunov stability for a minimal model of planar rigid body with two frictio...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	192,965
2401.03183	Exploring Defeasibility in Causal Reasoning	Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of strengthening arguments (supporters) or weakening arguments (defeaters), respectivel...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	420,006
2112.13320	Budget Sensitive Reannotation of Noisy Relation Classification Data Using Label Hierarchy	Large crowd-sourced datasets are often noisy and relation classification (RC) datasets are no exception. Reannotating the entire dataset is one probable solution however it is not always viable due to time and budget constraints. This paper addresses the problem of efficient reannotation of a large noisy dataset for th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	273,208
1809.04720	Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics	Learning robot tasks or controllers using deep reinforcement learning has been proven effective in simulations. Learning in simulation has several advantages. For example, one can fully control the simulated environment, including halting motions while performing computations. Another advantage when robots are involved...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	107,638
2304.02767	MethaneMapper: Spectral Absorption aware Hyperspectral Transformer for Methane Detection	Methane (CH$_4$) is the chief contributor to global climate change. Recent Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) has been very useful in quantitative mapping of methane emissions. Existing methods for analyzing this data are sensitive to local terrain conditions, often require manua...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	356,537
2210.10365	A sensor-to-pattern calibration framework for multi-modal industrial collaborative cells	Collaborative robotic industrial cells are workspaces where robots collaborate with human operators. In this context, safety is paramount, and for that a complete perception of the space where the collaborative robot is inserted is necessary. To ensure this, collaborative cells are equipped with a large set of sensors ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	324,893
1612.07771	Highway and Residual Networks learn Unrolled Iterative Estimation	The past year saw the introduction of new architectures such as Highway networks and Residual networks which, for the first time, enabled the training of feedforward networks with dozens to hundreds of layers using simple gradient descent. While depth of representation has been posited as a primary reason for their suc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	65,981
2306.06184	A Unified Model and Dimension for Interactive Estimation	We study an abstract framework for interactive learning called interactive estimation in which the goal is to estimate a target from its "similarity'' to points queried by the learner. We introduce a combinatorial measure called dissimilarity dimension which largely captures learnability in our model. We present a simp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,495
2310.11564	Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging	While Reinforcement Learning from Human Feedback (RLHF) aligns Large Language Models (LLMs) with general, aggregate human preferences, it is suboptimal for learning diverse, individual perspectives. In this work, we study Reinforcement Learning from Personalized Human Feedback (RLPHF) problem, wherein LLMs are aligned ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	400,684
1704.01926	Semantically-Guided Video Object Segmentation	This paper tackles the problem of semi-supervised video object segmentation, that is, segmenting an object in a sequence given its mask in the first frame. One of the main challenges in this scenario is the change of appearance of the objects of interest. Their semantics, on the other hand, do not vary. This paper inve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,351
1801.05388	UAV Offloading: Spectrum Trading Contract Design for UAV Assisted 5G Networks	Unmanned Aerial Vehicle (UAV) has been recognized as a promising way to assist future wireless communications due to its high flexibility of deployment and scheduling. In this paper, we focus on temporarily deployed UAVs that provide downlink data offloading in some regions under a macro base station (MBS). Since the m...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	88,446
1205.5141	There is no [21, 5, 14] code over F5	In this note, we demonstrate that there is no [21, 5, 14] code over F5.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,149
2107.14613	Incorporation of Deep Neural Network & Reinforcement Learning with Domain Knowledge	We present a study of the manners by which Domain information has been incorporated when building models with Neural Networks. Integrating space data is uniquely important to the development of Knowledge understanding model, as well as other fields that aid in understanding information by utilizing the human-machine in...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	248,526
2209.02655	Concentration of polynomial random matrices via Efron-Stein inequalities	Analyzing concentration of large random matrices is a common task in a wide variety of fields. Given independent random variables, many tools are available to analyze random matrices whose entries are linear in the variables, e.g. the matrix-Bernstein inequality. However, in many applications, we need to analyze random...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	316,270
2304.11249	eWaSR -- an embedded-compute-ready maritime obstacle detection network	Maritime obstacle detection is critical for safe navigation of autonomous surface vehicles (ASVs). While the accuracy of image-based detection methods has advanced substantially, their computational and memory requirements prohibit deployment on embedded devices. In this paper we analyze the currently best-performing m...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	359,735
2403.09577	The NeRFect Match: Exploring NeRF Features for Visual Localization	In this work, we propose the use of Neural Radiance Fields (NeRF) as a scene representation for visual localization. Recently, NeRF has been employed to enhance pose regression and scene coordinate regression models by augmenting the training database, providing auxiliary supervision through rendered images, or serving...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	437,822
2110.01532	Differentiable Spline Approximations	The paradigm of differentiable programming has significantly enhanced the scope of machine learning via the judicious use of gradient-based optimization. However, standard differentiable programming methods (such as autodiff) typically require that the machine learning models be differentiable, limiting their applicabi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	258,803
2103.06257	Maximum Entropy RL (Provably) Solves Some Robust RL Problems	Many potential applications of reinforcement learning (RL) require guarantees that the agent will perform well in the face of disturbances to the dynamics or reward function. In this paper, we prove theoretically that maximum entropy (MaxEnt) RL maximizes a lower bound on a robust RL objective, and thus can be used to ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	224,245
2106.00107	3D map creation using crowdsourced GNSS data	3D maps are increasingly useful for many applications such as drone navigation, emergency services, and urban planning. However, creating 3D maps and keeping them up-to-date using existing technologies, such as laser scanners, is expensive. This paper proposes and implements a novel approach to generate 2.5D (otherwise...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	237,984
2202.01723	Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks	The dynamics of systems biological processes are usually modeled by a system of ordinary differential equations (ODEs) with many unknown parameters that need to be inferred from noisy and sparse measurements. Here, we introduce systems-biology informed neural networks for parameter estimation by incorporating the syste...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,564
1510.05043	A cost function for similarity-based hierarchical clustering	The development of algorithms for hierarchical clustering has been hampered by a shortage of precise objective functions. To help address this situation, we introduce a simple cost function on hierarchies over a set of points, given pairwise similarities between those points. We show that this criterion behaves sensibl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	47,977
2308.12675	A Study of Age and Sex Bias in Multiple Instance Learning based Classification of Acute Myeloid Leukemia Subtypes	Accurate classification of Acute Myeloid Leukemia (AML) subtypes is crucial for clinical decision-making and patient care. In this study, we investigate the potential presence of age and sex bias in AML subtype classification using Multiple Instance Learning (MIL) architectures. To that end, we train multiple MIL model...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,635
2302.02785	An intelligent tutor for planning in large partially observable environments	AI can not only outperform people in many planning tasks, but it can also teach them how to plan better. A recent and promising approach to improving human decision-making is to create intelligent tutors that utilize AI to discover and teach optimal planning strategies automatically. Prior work has shown that this appr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	344,111
2411.13770	A Novel Passive Occupational Shoulder Exoskeleton With Adjustable Peak Assistive Torque Angle For Overhead Tasks	Objective: Overhead tasks are a primary inducement to work-related musculoskeletal disorders. Aiming to reduce shoulder physical loads, passive shoulder exoskeletons are increasingly prevalent in the industry due to their lightweight, affordability, and effectiveness. However, they can only accommodate a specific task ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	509,911
2401.05355	Developing a Resource-Constraint EdgeAI model for Surface Defect Detection	Resource constraints have restricted several EdgeAI applications to machine learning inference approaches, where models are trained on the cloud and deployed to the edge device. This poses challenges such as bandwidth, latency, and privacy associated with storing data off-site for model building. Training on the edge d...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	420,732
2403.13765	Towards Principled Representation Learning from Videos for Reinforcement Learning	We study pre-training representations for decision-making using video data, which is abundantly available for tasks such as game agents and software testing. Even though significant empirical advances have been made on this problem, a theoretical understanding remains absent. We initiate the theoretical investigation i...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	439,766
2103.09043	Inclined Quadrotor Landing using Deep Reinforcement Learning	Landing a quadrotor on an inclined surface is a challenging maneuver. The final state of any inclined landing trajectory is not an equilibrium, which precludes the use of most conventional control methods. We propose a deep reinforcement learning approach to design an autonomous landing controller for inclined surfaces...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	225,064
2008.06843	Learning Flow-based Feature Warping for Face Frontalization with Illumination Inconsistent Supervision	Despite recent advances in deep learning-based face frontalization methods, photo-realistic and illumination preserving frontal face synthesis is still challenging due to large pose and illumination discrepancy during training. We propose a novel Flow-based Feature Warping Model (FFWM) which can learn to synthesize pho...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,909
1904.04396	Hypersparse Neural Network Analysis of Large-Scale Internet Traffic	The Internet is transforming our society, necessitating a quantitative understanding of Internet traffic. Our team collects and curates the largest publicly available Internet traffic data containing 50 billion packets. Utilizing a novel hypersparse neural network analysis of "video" streams of this traffic using 10,00...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	true	127,021
1907.12393	To regulate or not: a social dynamics analysis of the race for AI supremacy	Rapid technological advancements in AI as well as the growing deployment of intelligent technologies in new application domains are currently driving the competition between businesses, nations and regions. This race for technological supremacy creates a complex ecology of choices that may lead to negative consequences...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	140,113
2007.03681	Fast Bayesian Estimation of Spatial Count Data Models	Spatial count data models are used to explain and predict the frequency of phenomena such as traffic accidents in geographically distinct entities such as census tracts or road segments. These models are typically estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation methods, which, however, are computati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	186,134
2407.12356	LTSim: Layout Transportation-based Similarity Measure for Evaluating Layout Generation	We introduce a layout similarity measure designed to evaluate the results of layout generation. While several similarity measures have been proposed in prior research, there has been a lack of comprehensive discussion about their behaviors. Our research uncovers that the majority of these measures are unable to handle ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,887
2501.12149	On the practical applicability of modern DFT functionals for chemical computations. Case study of DM21 applicability for geometry optimization	Density functional theory (DFT) is probably the most promising approach for quantum chemistry calculations considering its good balance between calculations precision and speed. In recent years, several neural network-based functionals have been developed for exchange-correlation energy approximation in DFT, DM21 devel...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	526,182
2306.07187	Video-to-Music Recommendation using Temporal Alignment of Segments	We study cross-modal recommendation of music tracks to be used as soundtracks for videos. This problem is known as the music supervision task. We build on a self-supervised system that learns a content association between music and video. In addition to the adequacy of content, adequacy of structure is crucial in music...	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	372,916
2405.03003	Parameter-Efficient Fine-Tuning with Discrete Fourier Transform	Low-rank adaptation~(LoRA) has recently gained much interest in fine-tuning foundation models. It effectively reduces the number of trainable parameters by incorporating low-rank matrices $A$ and $B$ to represent the weight change, i.e., $\Delta W=BA$. Despite LoRA's progress, it faces storage challenges when handling ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	452,013
2207.09455	To update or not to update? Neurons at equilibrium in deep models	Recent advances in deep learning optimization showed that, with some a-posteriori information on fully-trained models, it is possible to match the same performance by simply training a subset of their parameters. Such a discovery has a broad impact from theory to applications, driving the research towards methods to id...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	308,905
1510.07703	Full Duplex Assisted Inter-cell Interference Cancellation in Heterogeneous Networks	The paper studies the suppression of cross-tier inter-cell interference (ICI) generated by a macro base station (MBS) to pico user equipments (PUEs) in heterogeneous networks (HetNets). Different from existing ICI avoidance schemes such as enhanced ICI cancellation (eICIC) and coordinated beamforming, which generally o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	48,223
1706.06274	Learning Graphical Models Using Multiplicative Weights	We give a simple, multiplicative-weight update algorithm for learning undirected graphical models or Markov random fields (MRFs). The approach is new, and for the well-studied case of Ising models or Boltzmann machines, we obtain an algorithm that uses a nearly optimal number of samples and has quadratic running time (...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	75,653
2407.05480	Biomedical Nested NER with Large Language Model and UMLS Heuristics	In this paper, we present our system for the BioNNE English track, which aims to extract 8 types of biomedical nested named entities from biomedical text. We use a large language model (Mixtral 8x7B instruct) and ScispaCy NER model to identify entities in an article and build custom heuristics based on unified medical ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	470,996
2408.12870	Can AI Assistance Aid in the Grading of Handwritten Answer Sheets?	With recent advancements in artificial intelligence (AI), there has been growing interest in using state of the art (SOTA) AI solutions to provide assistance in grading handwritten answer sheets. While a few commercial products exist, the question of whether AI-assistance can actually reduce grading effort and time has...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	482,923
2102.06192	Adversarial Segmentation Loss for Sketch Colorization	We introduce a new method for generating color images from sketches or edge maps. Current methods either require some form of additional user-guidance or are limited to the "paired" translation approach. We argue that segmentation information could provide valuable guidance for sketch colorization. To this end, we prop...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	219,667
2011.06428	Discriminative, Generative and Self-Supervised Approaches for Target-Agnostic Learning	Supervised learning, characterized by both discriminative and generative learning, seeks to predict the values of single (or sometimes multiple) predefined target attributes based on a predefined set of predictor attributes. For applications where the information available and predictions to be made may vary from insta...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	206,245
2001.02334	$\mu$VulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection	Fine-grained software vulnerability detection is an important and challenging problem. Ideally, a detection system (or detector) not only should be able to detect whether or not a program contains vulnerabilities, but also should be able to pinpoint the type of a vulnerability in question. Existing vulnerability detect...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	159,709
1901.08810	Unsupervised speech representation learning using WaveNet autoencoders	We consider the task of unsupervised extraction of meaningful latent representations of speech by applying autoencoding neural networks to speech waveforms. The goal is to learn a representation able to capture high level semantic content from the signal, e.g.\ phoneme identities, while being invariant to confounding l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	119,583
1410.3248	One-shot Marton inner bound for classical-quantum broadcast channel	We consider the problem of communication over a classical-quantum broadcast channel with one sender and two receivers. Generalizing the classical inner bounds shown by Marton and the recent quantum asymptotic version shown by Savov and Wilde, we obtain one-shot inner bounds in the quantum setting. Our bounds are stated...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	36,691
1211.5494	Optimal design of PID controllers using the QFT method	An optimisation algorithm is proposed for designing PID controllers, which minimises the asymptotic open-loop gain of a system, subject to appropriate robust- stability and performance QFT constraints. The algorithm is simple and can be used to automate the loop-shaping step of the QFT design procedure. The effectivene...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	19,893
2302.00463	Uncertain Quality-Diversity: Evaluation methodology and new methods for Quality-Diversity in Uncertain Domains	Quality-Diversity optimisation (QD) has proven to yield promising results across a broad set of applications. However, QD approaches struggle in the presence of uncertainty in the environment, as it impacts their ability to quantify the true performance and novelty of solutions. This problem has been highlighted multip...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	343,225
2006.07900	ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification	Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision trees to enable resource-efficient classification on a neural im...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,997
2009.00739	Non-asymptotic Identification of Linear Dynamical Systems Using Multiple Trajectories	This paper considers the problem of linear time-invariant (LTI) system identification using input/output data. Recent work has provided non-asymptotic results on partially observed LTI system identification using a single trajectory but is only suitable for stable systems. We provide finite-time analysis for learning M...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	194,122
2205.10055	A Case of Exponential Convergence Rates for SVM	Classification is often the first problem described in introductory machine learning classes. Generalization guarantees of classification have historically been offered by Vapnik-Chervonenkis theory. Yet those guarantees are based on intractable algorithms, which has led to the theory of surrogate methods in classifica...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	297,537
0809.1963	Materialized View Selection by Query Clustering in XML Data Warehouses	XML data warehouses form an interesting basis for decision-support applications that exploit complex data. However, native XML database management systems currently bear limited performances and it is necessary to design strategies to optimize them. In this paper, we propose an automatic strategy for the selection of X...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	2,329
2006.09904	Learning Colour Representations of Search Queries	Image search engines rely on appropriately designed ranking features that capture various aspects of the content semantics as well as the historic popularity. In this work, we consider the role of colour in this relevance matching process. Our work is motivated by the observation that a significant fraction of user que...	false	false	false	false	false	true	true	false	false	false	false	true	false	false	false	false	false	false	182,695
1905.09152	Multi-View Large-Scale Bundle Adjustment Method for High-Resolution Satellite Images	Given enough multi-view image corresponding points (also called tie points) and ground control points (GCP), bundle adjustment for high-resolution satellite images is used to refine the orientations or most often used geometric parameters Rational Polynomial Coefficients (RPC) of each satellite image in a unified geode...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	131,659
2203.02502	No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds	Centroid based clustering methods such as k-means, k-medoids and k-centers are heavily applied as a go-to tool in exploratory data analysis. In many cases, those methods are used to obtain representative centroids of the data manifold for visualization or summarization of a dataset. Real world datasets often contain in...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	283,767
2404.15564	Guided AbsoluteGrad: Magnitude of Gradients Matters to Explanation's Localization and Saliency	This paper proposes a new gradient-based XAI method called Guided AbsoluteGrad for saliency map explanations. We utilize both positive and negative gradient magnitudes and employ gradient variance to distinguish the important areas for noise deduction. We also introduce a novel evaluation metric named ReCover And Predi...	true	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	449,138

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