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
2308.14191	SketchDreamer: Interactive Text-Augmented Creative Sketch Ideation	Artificial Intelligence Generated Content (AIGC) has shown remarkable progress in generating realistic images. However, in this paper, we take a step "backward" and address AIGC for the most rudimentary visual modality of human sketches. Our objective is on the creative nature of sketches, and that creative sketching s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,229
1804.05886	Subcarrier-Interlaced FDD for Faster-than-TDD Channel Tracking in Massive MIMO Systems	Canonical Massive MIMO uses time division duplex (TDD) to exploit channel reciprocity within the coherence time, avoiding feedback of channel state information (CSI), as is required for precoding at the base station. We extend the idea of exploiting reciprocity to the coherence bandwidth, allocating subcarriers of a mu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	95,164
2307.14783	Emotion4MIDI: a Lyrics-based Emotion-Labeled Symbolic Music Dataset	We present a new large-scale emotion-labeled symbolic music dataset consisting of 12k MIDI songs. To create this dataset, we first trained emotion classification models on the GoEmotions dataset, achieving state-of-the-art results with a model half the size of the baseline. We then applied these models to lyrics from t...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	382,052
2202.10099	Simplified Learning of CAD Features Leveraging a Deep Residual Autoencoder	In the domain of computer vision, deep residual neural networks like EfficientNet have set new standards in terms of robustness and accuracy. One key problem underlying the training of deep neural networks is the immanent lack of a sufficient amount of training data. The problem worsens especially if labels cannot be g...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	281,416
2305.14579	Real-Time Idling Vehicles Detection using Combined Audio-Visual Deep Learning	Combustion vehicle emissions contribute to poor air quality and release greenhouse gases into the atmosphere, and vehicle pollution has been associated with numerous adverse health effects. Roadways with extensive waiting and/or passenger drop off, such as schools and hospital drop-off zones, can result in high inciden...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	367,105
2407.07472	Rectifier: Code Translation with Corrector via LLMs	Software migration is garnering increasing attention with the evolution of software and society. Early studies mainly relied on handcrafted translation rules to translate between two languages, the translation process is error-prone and time-consuming. In recent years, researchers have begun to explore the use of pre-t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	471,776
1805.12164	What the Vec? Towards Probabilistically Grounded Embeddings	Word2Vec (W2V) and GloVe are popular, fast and efficient word embedding algorithms. Their embeddings are widely used and perform well on a variety of natural language processing tasks. Moreover, W2V has recently been adopted in the field of graph embedding, where it underpins several leading algorithms. However, despit...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	99,102
2111.04017	Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation	We consider a new problem of adapting a human mesh reconstruction model to out-of-domain streaming videos, where performance of existing SMPL-based models are significantly affected by the distribution shift represented by different camera parameters, bone lengths, backgrounds, and occlusions. We tackle this problem th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	265,348
2411.10699	Hierarchical Adaptive Motion Planning with Nonlinear Model Predictive Control for Safety-Critical Collaborative Loco-Manipulation	As legged robots take on roles in industrial and autonomous construction, collaborative loco-manipulation is crucial for handling large and heavy objects that exceed the capabilities of a single robot. However, ensuring the safety of these multi-robot tasks is essential to prevent accidents and guarantee reliable opera...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	508,753
2308.02038	CLGT: A Graph Transformer for Student Performance Prediction in Collaborative Learning	Modeling and predicting the performance of students in collaborative learning paradigms is an important task. Most of the research presented in literature regarding collaborative learning focuses on the discussion forums and social learning networks. There are only a few works that investigate how students interact wit...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	383,460
2207.10702	Efficient model compression with Random Operation Access Specific Tile (ROAST) hashing	Advancements in deep learning are often associated with increasing model sizes. The model size dramatically affects the deployment cost and latency of deep models. For instance, models like BERT cannot be deployed on edge devices and mobiles due to their sheer size. As a result, most advances in Deep Learning are yet t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	309,350
2307.07264	On Interpolating Experts and Multi-Armed Bandits	Learning with expert advice and multi-armed bandit are two classic online decision problems which differ on how the information is observed in each round of the game. We study a family of problems interpolating the two. For a vector $\mathbf{m}=(m_1,\dots,m_K)\in \mathbb{N}^K$, an instance of $\mathbf{m}$-MAB indicates...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	379,338
2106.04707	Job Dispatching Policies for Queueing Systems with Unknown Service Rates	In multi-server queueing systems where there is no central queue holding all incoming jobs, job dispatching policies are used to assign incoming jobs to the queue at one of the servers. Classic job dispatching policies such as join-the-shortest-queue and shortest expected delay assume that the service rates and queue l...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	239,819
2202.12219	Debugging Differential Privacy: A Case Study for Privacy Auditing	Differential Privacy can provide provable privacy guarantees for training data in machine learning. However, the presence of proofs does not preclude the presence of errors. Inspired by recent advances in auditing which have been used for estimating lower bounds on differentially private algorithms, here we show that a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	282,150
2406.17232	Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks	Creating human-like large language model (LLM) agents is crucial for faithful social simulation. Having LLMs role-play based on demographic information sometimes improves human likeness but often does not. This study assessed whether LLM alignment with human behavior can be improved by integrating information from empi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	467,474
2212.06636	Categorical Tools for Natural Language Processing	This thesis develops the translation between category theory and computational linguistics as a foundation for natural language processing. The three chapters deal with syntax, semantics and pragmatics. First, string diagrams provide a unified model of syntactic structures in formal grammars. Second, functors compute s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	336,173
2302.13485	FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning	Federated learning (FL) has emerged as a new paradigm for privacy-preserving computation in recent years. Unfortunately, FL faces two critical challenges that hinder its actual performance: data distribution heterogeneity and high resource costs brought by large foundation models. Specifically, the non-IID data in diff...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	347,966
1912.02975	Observational Overfitting in Reinforcement Learning	A major component of overfitting in model-free reinforcement learning (RL) involves the case where the agent may mistakenly correlate reward with certain spurious features from the observations generated by the Markov Decision Process (MDP). We provide a general framework for analyzing this scenario, which we use to de...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	156,484
2108.11119	Product-oriented Machine Translation with Cross-modal Cross-lingual Pre-training	Translating e-commercial product descriptions, a.k.a product-oriented machine translation (PMT), is essential to serve e-shoppers all over the world. However, due to the domain specialty, the PMT task is more challenging than traditional machine translation problems. Firstly, there are many specialized jargons in the p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,101
2409.03655	Privacy versus Emotion Preservation Trade-offs in Emotion-Preserving Speaker Anonymization	Advances in speech technology now allow unprecedented access to personally identifiable information through speech. To protect such information, the differential privacy field has explored ways to anonymize speech while preserving its utility, including linguistic and paralinguistic aspects. However, anonymizing speech...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	486,115
2112.03183	Modification-Fair Cluster Editing	The classic Cluster Editing problem (also known as Correlation Clustering) asks to transform a given graph into a disjoint union of cliques (clusters) by a small number of edge modifications. When applied to vertex-colored graphs (the colors representing subgroups), standard algorithms for the NP-hard Cluster Editing p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	270,110
1604.08667	A Bio-Inspired Tensegrity Manipulator with Multi-DOF, Structurally Compliant Joints	Most traditional robotic mechanisms feature inelastic joints that are unable to robustly handle large deformations and off-axis moments. As a result, the applied loads are transferred rigidly throughout the entire structure. The disadvantage of this approach is that the exerted leverage is magnified at each subsequent ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	55,234
2204.07524	Neural Structured Prediction for Inductive Node Classification	This paper studies node classification in the inductive setting, i.e., aiming to learn a model on labeled training graphs and generalize it to infer node labels on unlabeled test graphs. This problem has been extensively studied with graph neural networks (GNNs) by learning effective node representations, as well as tr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	291,737
1711.07581	Spec-QP: Speculative Query Planning for Joins over Knowledge Graphs	Organisations store huge amounts of data from multiple heterogeneous sources in the form of Knowledge Graphs (KGs). One of the ways to query these KGs is to use SPARQL queries over a database engine. Since SPARQL follows exact match semantics, the queries may return too few or no results. Recent works have proposed que...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	85,018
2206.11339	Precipitation event-based networks: an analysis of the relations between network metrics and meteorological properties	The study of complex systems in nature is essential to understand the interactions between different elements and how they influence one another. Complex network theory is a powerful tool that helps us to analyze these interactions and gain insights into the behavior of such systems. Surprisingly, this theory has been ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	304,232
2402.03896	Convincing Rationales for Visual Question Answering Reasoning	Visual Question Answering (VQA) is a challenging task of predicting the answer to a question about the content of an image. It requires deep understanding of both the textual question and visual image. Prior works directly evaluate the answering models by simply calculating the accuracy of the predicted answers. Howeve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	427,237
2202.11425	Multi-view Intent Disentangle Graph Networks for Bundle Recommendation	Bundle recommendation aims to recommend the user a bundle of items as a whole. Nevertheless, they usually neglect the diversity of the user's intents on adopting items and fail to disentangle the user's intents in representations. In the real scenario of bundle recommendation, a user's intent may be naturally distribut...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	281,883
2405.02340	A Comprehensive Approach to Carbon Dioxide Emission Analysis in High Human Development Index Countries using Statistical and Machine Learning Techniques	Reducing Carbon dioxide (CO2) emission is vital at both global and national levels, given their significant role in exacerbating climate change. CO2 emission, stemming from a variety of industrial and economic activities, are major contributors to the greenhouse effect and global warming, posing substantial obstacles i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	451,723
0806.1316	The end of Sleeping Beauty's nightmare	The way a rational agent changes her belief in certain propositions/hypotheses in the light of new evidence lies at the heart of Bayesian inference. The basic natural assumption, as summarized in van Fraassen's Reflection Principle ([1984]), would be that in the absence of new evidence the belief should not change. Yet...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	1,887
1911.07758	Inexact Primal-Dual Gradient Projection Methods for Nonlinear Optimization on Convex Set	In this paper, we propose a novel primal-dual inexact gradient projection method for nonlinear optimization problems with convex-set constraint. This method only needs inexact computation of the projections onto the convex set for each iteration, consequently reducing the computational cost for projections per iteratio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,962
2305.14163	Leveraging Open Information Extraction for More Robust Domain Transfer of Event Trigger Detection	Event detection is a crucial information extraction task in many domains, such as Wikipedia or news. The task typically relies on trigger detection (TD) -- identifying token spans in the text that evoke specific events. While the notion of triggers should ideally be universal across domains, domain transfer for TD from...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	366,884
2502.11298	Integrating Language Models for Enhanced Network State Monitoring in DRL-Based SFC Provisioning	Efficient Service Function Chain (SFC) provisioning and Virtual Network Function (VNF) placement are critical for enhancing network performance in modern architectures such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). While Deep Reinforcement Learning (DRL) aids decision-making in dyn...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	534,291
2305.06038	Secure Block Joint Source-Channel Coding with Sequential Encoding	We extend the results of Ghourchian et al. [IEEE JSAIT-2021], to joint source-channel coding with eavesdropping. Our work characterizes the sequential encoding process using the cumulative rate distribution functions (CRDF) and includes a security constraint using the cumulative leakage distribution functions (CLF). Th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	363,381
2102.00498	Integration of activation maps of epicardial veins in computational cardiac electrophysiology	In this work we address the issue of validating the monodomain equation used in combination with the Bueno-Orovio ionic model for the prediction of the activation times in cardiac electro-physiology of the left ventricle. To this aim, we consider our patients who suffered from Left Bundle Branch Block (LBBB). We use ac...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	217,805
2406.07784	Characterization of Acoustic Losses in Interdigitated VHF to mmWave Piezoelectric M/NEMS Resonators	This work reports on a technology-agnostic and frequency-independent methodology combining a-priori modeling, Finite Element Analysis (FEA), and experimental results for the characterization of acoustic losses in interdigitated piezoelectric micro- and nano-electromechanical (M/NEMS) resonators. The proposed approach m...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	463,204
2408.07553	Remote Tube-based MPC for Tracking Over Lossy Networks	This paper addresses the problem of controlling constrained systems subject to disturbances in the case where controller and system are connected over a lossy network. To do so, we propose a novel framework that splits the concept of tube-based model predictive control into two parts. One runs locally on the system and...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	480,637
2407.05954	Causality-driven Sequence Segmentation for Enhancing Multiphase Industrial Process Data Analysis and Soft Sensing	The dynamic characteristics of multiphase industrial processes present significant challenges in the field of industrial big data modeling. Traditional soft sensing models frequently neglect the process dynamics and have difficulty in capturing transient phenomena like phase transitions. To address this issue, this art...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	471,188
2102.00837	Machine learning pipeline for battery state of health estimation	Lithium-ion batteries are ubiquitous in modern day applications ranging from portable electronics to electric vehicles. Irrespective of the application, reliable real-time estimation of battery state of health (SOH) by on-board computers is crucial to the safe operation of the battery, ultimately safeguarding asset int...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	217,928
2211.00576	Event Tables for Efficient Experience Replay	Experience replay (ER) is a crucial component of many deep reinforcement learning (RL) systems. However, uniform sampling from an ER buffer can lead to slow convergence and unstable asymptotic behaviors. This paper introduces Stratified Sampling from Event Tables (SSET), which partitions an ER buffer into Event Tables,...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	327,922
1601.07865	Grid Energy Consumption and QoS Tradeoff in Hybrid Energy Supply Wireless Networks	Hybrid energy supply (HES) wireless networks have recently emerged as a new paradigm to enable green networks, which are powered by both the electric grid and harvested renewable energy. In this paper, we will investigate two critical but conflicting design objectives of HES networks, i.e., the grid energy consumption ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,471
2304.05475	Failure Probability Estimation and Detection of Failure Surfaces via Adaptive Sequential Decomposition of the Design Domain	We propose an algorithm for an optimal adaptive selection of points from the design domain of input random variables that are needed for an accurate estimation of failure probability and the determination of the boundary between safe and failure domains. The method is particularly useful when each evaluation of the per...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	357,634
2107.06840	Mixing Human Demonstrations with Self-Exploration in Experience Replay for Deep Reinforcement Learning	We investigate the effect of using human demonstration data in the replay buffer for Deep Reinforcement Learning. We use a policy gradient method with a modified experience replay buffer where a human demonstration experience is sampled with a given probability. We analyze different ratios of using demonstration data i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	246,211
1906.09811	Blind decoding in $\alpha$-Stable noise: An online learning approach	A novel method for performing error control coding in Symmetric $\alpha-$Stable noise environments without any prior knowledge about the value of $\alpha$ is introduced. We use an online learning framework which employs multiple distributions to decode the received block and then combines these results based on the pas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	136,277
2412.18053	Neuron Empirical Gradient: Discovering and Quantifying Neurons Global Linear Controllability	Although feed-forward neurons in pre-trained language models (PLMs) can store knowledge and their importance in influencing model outputs has been studied, existing work focuses on finding a limited set of neurons and analyzing their relative importance. However, the global quantitative role of activation values in sha...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	520,232
2208.12771	NeuralSI: Structural Parameter Identification in Nonlinear Dynamical Systems	Structural monitoring for complex built environments often suffers from mismatch between design, laboratory testing, and actual built parameters. Additionally, real-world structural identification problems encounter many challenges. For example, the lack of accurate baseline models, high dimensionality, and complex mul...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	314,843
1809.08013	Towards a Mini-App for Smoothed Particle Hydrodynamics at Exascale	The smoothed particle hydrodynamics (SPH) technique is a purely Lagrangian method, used in numerical simulations of fluids in astrophysics and computational fluid dynamics, among many other fields. SPH simulations with detailed physics represent computationally-demanding calculations. The parallelization of SPH codes i...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	108,409
2310.01837	Extending CAM-based XAI methods for Remote Sensing Imagery Segmentation	Current AI-based methods do not provide comprehensible physical interpretations of the utilized data, extracted features, and predictions/inference operations. As a result, deep learning models trained using high-resolution satellite imagery lack transparency and explainability and can be merely seen as a black box, wh...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	396,598
1812.07768	Modular meta-learning in abstract graph networks for combinatorial generalization	Modular meta-learning is a new framework that generalizes to unseen datasets by combining a small set of neural modules in different ways. In this work we propose abstract graph networks: using graphs as abstractions of a system's subparts without a fixed assignment of nodes to system subparts, for which we would need ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	116,880
2007.02771	Certifying Decision Trees Against Evasion Attacks by Program Analysis	Machine learning has proved invaluable for a range of different tasks, yet it also proved vulnerable to evasion attacks, i.e., maliciously crafted perturbations of input data designed to force mispredictions. In this paper we propose a novel technique to verify the security of decision tree models against evasion attac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	185,851
2006.14410	Modelling of Variable-Speed Refrigeration for Fast-Frequency Control in Low-InertiaSystems	In modern power systems, shiftable loads contribute to the flexibility needed to increase robustness and ensure security. Thermal loads are among the most promising candidates for providing such service due to the large thermal storage time constants. This paper demonstrates the use of Variable-Speed Refrigeration (VSR...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	184,216
1610.04336	MML is not consistent for Neyman-Scott	Strict Minimum Message Length (SMML) is an information-theoretic statistical inference method widely cited (but only with informal arguments) as providing estimations that are consistent for general estimation problems. It is, however, almost invariably intractable to compute, for which reason only approximations of it...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	62,376
2411.02229	FewViewGS: Gaussian Splatting with Few View Matching and Multi-stage Training	The field of novel view synthesis from images has seen rapid advancements with the introduction of Neural Radiance Fields (NeRF) and more recently with 3D Gaussian Splatting. Gaussian Splatting became widely adopted due to its efficiency and ability to render novel views accurately. While Gaussian Splatting performs we...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	505,408
2012.01930	Learning Explainable Interventions to Mitigate HIV Transmission in Sex Workers Across Five States in India	Female sex workers(FSWs) are one of the most vulnerable and stigmatized groups in society. As a result, they often suffer from a lack of quality access to care. Grassroot organizations engaged in improving health services are often faced with the challenge of improving the effectiveness of interventions due to complex ...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	209,577
2006.02619	Integrating Machine Learning with Physics-Based Modeling	Machine learning is poised as a very powerful tool that can drastically improve our ability to carry out scientific research. However, many issues need to be addressed before this becomes a reality. This article focuses on one particular issue of broad interest: How can we integrate machine learning with physics-based ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	180,092
2006.10408	Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax	Solving long-tail large vocabulary object detection with deep learning based models is a challenging and demanding task, which is however under-explored.In this work, we provide the first systematic analysis on the underperformance of state-of-the-art models in front of long-tail distribution. We find existing detectio...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	182,877
1205.5134	Iterated Space-Time Code Constructions from Cyclic Algebras	We propose a full-rate iterated space-time code construction, to design 2n-dimensional codes from n-dimensional cyclic algebra based codes. We give a condition to determine whether the resulting codes satisfy the full-diversity property, and study their maximum likelihood decoding complexity with respect to sphere deco...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,148
2501.08347	SCOT: Self-Supervised Contrastive Pretraining For Zero-Shot Compositional Retrieval	Compositional image retrieval (CIR) is a multimodal learning task where a model combines a query image with a user-provided text modification to retrieve a target image. CIR finds applications in a variety of domains including product retrieval (e-commerce) and web search. Existing methods primarily focus on fully-supe...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	524,732
1504.07665	Elastic properties of mono- and polydisperse two-dimensional crystals of hard--core repulsive Yukawa particles	Monte Carlo simulations of mono-- and polydisperse two--dimensional crystals are reported. The particles in the studied system, interacting through hard--core repulsive Yukawa potential, form a solid phase of hexagonal lattice. The elastic properties of crystalline Yukawa systems are determined in the $NpT$ ensemble wi...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	42,565
2005.13107	VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics	We propose VarFA, a variational inference factor analysis framework that extends existing factor analysis models for educational data mining to efficiently output uncertainty estimation in the model's estimated factors. Such uncertainty information is useful, for example, for an adaptive testing scenario, where additio...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	178,904
2409.01449	Real-Time Recurrent Learning using Trace Units in Reinforcement Learning	Recurrent Neural Networks (RNNs) are used to learn representations in partially observable environments. For agents that learn online and continually interact with the environment, it is desirable to train RNNs with real-time recurrent learning (RTRL); unfortunately, RTRL is prohibitively expensive for standard RNNs. A...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	485,339
2305.19915	Source Code Data Augmentation for Deep Learning: A Survey	The increasingly popular adoption of deep learning models in many critical source code tasks motivates the development of data augmentation (DA) techniques to enhance training data and improve various capabilities (e.g., robustness and generalizability) of these models. Although a series of DA methods have been propose...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	369,735
0807.2701	A Cutting Plane Method based on Redundant Rows for Improving Fractional Distance	In this paper, an idea of the cutting plane method is employed to improve the fractional distance of a given binary parity check matrix. The fractional distance is the minimum weight (with respect to l1-distance) of vertices of the fundamental polytope. The cutting polytope is defined based on redundant rows of the par...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,076
2302.08764	Adversarial Contrastive Distillation with Adaptive Denoising	Adversarial Robustness Distillation (ARD) is a novel method to boost the robustness of small models. Unlike general adversarial training, its robust knowledge transfer can be less easily restricted by the model capacity. However, the teacher model that provides the robustness of knowledge does not always make correct p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	346,175
1703.02363	Qualitative Assessment of Recurrent Human Motion	Smartphone applications designed to track human motion in combination with wearable sensors, e.g., during physical exercising, raised huge attention recently. Commonly, they provide quantitative services, such as personalized training instructions or the counting of distances. But qualitative monitoring and assessment ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	69,540
2405.14242	M2ANET: Mobile Malaria Attention Network for efficient classification of plasmodium parasites in blood cells	Malaria is a life-threatening infectious disease caused by Plasmodium parasites, which poses a significant public health challenge worldwide, particularly in tropical and subtropical regions. Timely and accurate detection of malaria parasites in blood cells is crucial for effective treatment and control of the disease....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	456,327
1105.5174	Symmetry Reduction of Optimal Control Systems and Principal Connections	This paper explores the role of symmetries and reduction in nonlinear control and optimal control systems. The focus of the paper is to give a geometric framework of symmetry reduction of optimal control systems as well as to show how to obtain explicit expressions of the reduced system by exploiting the geometry. In p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	10,499
2309.01448	Hundreds Guide Millions: Adaptive Offline Reinforcement Learning with Expert Guidance	Offline reinforcement learning (RL) optimizes the policy on a previously collected dataset without any interactions with the environment, yet usually suffers from the distributional shift problem. To mitigate this issue, a typical solution is to impose a policy constraint on a policy improvement objective. However, exi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	389,691
2412.16213	AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models	The increasing deployment of AI models in critical applications has exposed them to significant risks from adversarial attacks. While adversarial vulnerabilities in 2D vision models have been extensively studied, the threat landscape for 3D generative models, such as Neural Radiance Fields (NeRF), remains underexplored...	false	false	false	false	true	false	false	false	false	false	false	true	false	true	false	false	false	true	519,416
2305.06817	THUIR@COLIEE 2023: More Parameters and Legal Knowledge for Legal Case Entailment	This paper describes the approach of the THUIR team at the COLIEE 2023 Legal Case Entailment task. This task requires the participant to identify a specific paragraph from a given supporting case that entails the decision for the query case. We try traditional lexical matching methods and pre-trained language models wi...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	363,673
2309.10068	A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes	The Gaussian process (GP) is a popular statistical technique for stochastic function approximation and uncertainty quantification from data. GPs have been adopted into the realm of machine learning in the last two decades because of their superior prediction abilities, especially in data-sparse scenarios, and their inh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	392,850
1802.07854	Driver Hand Localization and Grasp Analysis: A Vision-based Real-time Approach	Extracting hand regions and their grasp information from images robustly in real-time is critical for occupants' safety and in-vehicular infotainment applications. It must however, be noted that naturalistic driving scenes suffer from rapidly changing illumination and occlusion. This is aggravated by the fact that hand...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	90,972
1702.07959	Supervised Learning of Labeled Pointcloud Differences via Cover-Tree Entropy Reduction	We introduce a new algorithm, called CDER, for supervised machine learning that merges the multi-scale geometric properties of Cover Trees with the information-theoretic properties of entropy. CDER applies to a training set of labeled pointclouds embedded in a common Euclidean space. If typical pointclouds correspondin...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	68,877
1103.1991	Connectivity of Large Scale Networks: Emergence of Unique Unbounded Component	This paper studies networks where all nodes are distributed on a unit square $A\triangleq[(-1/2,1/2)^{2}$ following a Poisson distribution with known density $\rho$ and a pair of nodes separated by an Euclidean distance $x$ are directly connected with probability $g(\frac{x}{r_{\rho}})$, independent of the event that a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	9,556
2312.12558	Sample Efficient Reinforcement Learning with Partial Dynamics Knowledge	The problem of sample complexity of online reinforcement learning is often studied in the literature without taking into account any partial knowledge about the system dynamics that could potentially accelerate the learning process. In this paper, we study the sample complexity of online Q-learning methods when some pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	417,001
2303.01577	DeepLens: Interactive Out-of-distribution Data Detection in NLP Models	Machine Learning (ML) has been widely used in Natural Language Processing (NLP) applications. A fundamental assumption in ML is that training data and real-world data should follow a similar distribution. However, a deployed ML model may suffer from out-of-distribution (OOD) issues due to distribution shifts in the rea...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	349,024
2105.09058	Revisiting Data Compression in Column-Stores	Data compression is widely used in contemporary column-oriented DBMSes to lower space usage and to speed up query processing. Pioneering systems have introduced compression to tackle the disk bandwidth bottleneck by trading CPU processing power for it. The main issue of this is a trade-off between the compression ratio...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	235,956
2112.08723	Distilled Dual-Encoder Model for Vision-Language Understanding	We propose a cross-modal attention distillation framework to train a dual-encoder model for vision-language understanding tasks, such as visual reasoning and visual question answering. Dual-encoder models have a faster inference speed than fusion-encoder models and enable the pre-computation of images and text during i...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	271,908
2402.10088	Deep hybrid models: infer and plan in a dynamic world	In order to determine an optimal plan for a complex task, one often deals with dynamic and hierarchical relationships between several entities. Traditionally, such problems are tackled with optimal control, which relies on the optimization of cost functions; instead, a recent biologically-motivated proposal casts plann...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	429,811
2112.12638	RumbleML: program the lakehouse with JSONiq	Lakehouse systems have reached in the past few years unprecedented size and heterogeneity and have been embraced by many industry players. However, they are often difficult to use as they lack the declarative language and optimization possibilities of relational engines. This paper introduces RumbleML, a high-level, de...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	273,021
2208.02162	One Node at a Time: Node-Level Network Classification	Network classification aims to group networks (or graphs) into distinct categories based on their structure. We study the connection between classification of a network and of its constituent nodes, and whether nodes from networks in different groups are distinguishable based on structural node characteristics such as ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	311,395
1902.03830	Semantic Hierarchical Priors for Intrinsic Image Decomposition	Intrinsic Image Decomposition (IID) is a challenging and interesting computer vision problem with various applications in several fields. We present novel semantic priors and an integrated approach for single image IID that involves analyzing image at three hierarchical context levels. Local context priors capture scen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	121,210
2206.12790	APPFLChain: A Privacy Protection Distributed Artificial-Intelligence Architecture Based on Federated Learning and Consortium Blockchain	Recent research in Internet of things has been widely applied for industrial practices, fostering the exponential growth of data and connected devices. Henceforth, data-driven AI models would be accessed by different parties through certain data-sharing policies. However, most of the current training procedures rely on...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	true	false	304,735
2411.05174	Inverse Transition Learning: Learning Dynamics from Demonstrations	We consider the problem of estimating the transition dynamics $T^*$ from near-optimal expert trajectories in the context of offline model-based reinforcement learning. We develop a novel constraint-based method, Inverse Transition Learning, that treats the limited coverage of the expert trajectories as a \emph{feature}...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	506,562
1907.12581	Improved mutual information measure for classification and community detection	The information theoretic quantity known as mutual information finds wide use in classification and community detection analyses to compare two classifications of the same set of objects into groups. In the context of classification algorithms, for instance, it is often used to compare discovered classes to known groun...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	140,149
2108.09342	Design of Novel 3T Ternary DRAM with Single Word-Line using CNTFET	Ternary logic system is the most promising and pursued alternate to the prevailing binary logic systems due to the energy efficiency of circuits following reduced circuit complexity and chip area. In this paper, we have proposed a ternary 3-Transistor Dynamic Random-Access Memory (3T-DRAM) cell using a single word-line...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	251,564
2306.12107	A new color image secret sharing protocol	Visual cryptography aims to protect images against their possible illegitimate use. Thus, one can cipher, hash, or add watermarks for protecting copyright, among others. In this paper we provide a new solution to the problem of secret sharing for the case when the secret is an image. Our method combines the Shamir sche...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	374,834
2107.07596	Depth Estimation from Monocular Images and Sparse radar using Deep Ordinal Regression Network	We integrate sparse radar data into a monocular depth estimation model and introduce a novel preprocessing method for reducing the sparseness and limited field of view provided by radar. We explore the intrinsic error of different radar modalities and show our proposed method results in more data points with reduced er...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	246,466
2412.07618	Adapting to Non-Stationary Environments: Multi-Armed Bandit Enhanced Retrieval-Augmented Generation on Knowledge Graphs	Despite the superior performance of Large language models on many NLP tasks, they still face significant limitations in memorizing extensive world knowledge. Recent studies have demonstrated that leveraging the Retrieval-Augmented Generation (RAG) framework, combined with Knowledge Graphs that encapsulate extensive fac...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	515,735
2304.06275	Noisy Correspondence Learning with Meta Similarity Correction	Despite the success of multimodal learning in cross-modal retrieval task, the remarkable progress relies on the correct correspondence among multimedia data. However, collecting such ideal data is expensive and time-consuming. In practice, most widely used datasets are harvested from the Internet and inevitably contain...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	357,918
2310.16941	Exploring Behavior Discovery Methods for Heterogeneous Swarms of Limited-Capability Robots	We study the problem of determining the emergent behaviors that are possible given a functionally heterogeneous swarm of robots with limited capabilities. Prior work has considered behavior search for homogeneous swarms and proposed the use of novelty search over either a hand-specified or learned behavior space follow...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	true	false	false	false	402,925
1902.04247	PAC-Bayes Analysis of Sentence Representation	Learning sentence vectors from an unlabeled corpus has attracted attention because such vectors can represent sentences in a lower dimensional and continuous space. Simple heuristics using pre-trained word vectors are widely applied to machine learning tasks. However, they are not well understood from a theoretical per...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	121,300
2411.05596	Machine learning-driven Anomaly Detection and Forecasting for Euclid Space Telescope Operations	State-of-the-art space science missions increasingly rely on automation due to spacecraft complexity and the costs of human oversight. The high volume of data, including scientific and telemetry data, makes manual inspection challenging. Machine learning offers significant potential to meet these demands. The Euclid ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	506,719
2104.14837	RobustFusion: Robust Volumetric Performance Reconstruction under Human-object Interactions from Monocular RGBD Stream	High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applications. However, recent advances still fail to provide reliable performance reconstruction, suffering from challenging interaction patterns ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,966
2010.03701	Differentially Private Deep Learning with Direct Feedback Alignment	Standard methods for differentially private training of deep neural networks replace back-propagated mini-batch gradients with biased and noisy approximations to the gradient. These modifications to training often result in a privacy-preserving model that is significantly less accurate than its non-private counterpart....	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	199,492
2007.14641	Generalization Properties of Optimal Transport GANs with Latent Distribution Learning	The Generative Adversarial Networks (GAN) framework is a well-established paradigm for probability matching and realistic sample generation. While recent attention has been devoted to studying the theoretical properties of such models, a full theoretical understanding of the main building blocks is still missing. Focus...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	189,465
2308.04566	Single-Sentence Reader: A Novel Approach for Addressing Answer Position Bias	Machine Reading Comprehension (MRC) models tend to take advantage of spurious correlations (also known as dataset bias or annotation artifacts in the research community). Consequently, these models may perform the MRC task without fully comprehending the given context and question, which is undesirable since it may res...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	384,457
1803.03910	A pathway-based kernel boosting method for sample classification using genomic data	The analysis of cancer genomic data has long suffered "the curse of dimensionality". Sample sizes for most cancer genomic studies are a few hundreds at most while there are tens of thousands of genomic features studied. Various methods have been proposed to leverage prior biological knowledge, such as pathways, to more...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	92,353
2010.14323	Sub-sampling for Efficient Non-Parametric Bandit Exploration	In this paper we propose the first multi-armed bandit algorithm based on re-sampling that achieves asymptotically optimal regret simultaneously for different families of arms (namely Bernoulli, Gaussian and Poisson distributions). Unlike Thompson Sampling which requires to specify a different prior to be optimal in eac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	203,414
2008.06908	Visually Aware Skip-Gram for Image Based Recommendations	The visual appearance of a product significantly influences purchase decisions on e-commerce websites. We propose a novel framework VASG (Visually Aware Skip-Gram) for learning user and product representations in a common latent space using product image features. Our model is an amalgamation of the Skip-Gram architect...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	191,931
2105.08855	Effective Attention Sheds Light On Interpretability	An attention matrix of a transformer self-attention sublayer can provably be decomposed into two components and only one of them (effective attention) contributes to the model output. This leads us to ask whether visualizing effective attention gives different conclusions than interpretation of standard attention. Usin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	235,887

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