Most Cited 2025 "numerical reconstruction" Papers

Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm Identification

Kapilan Balagopalan, Tuan Nguyen, Yao Zhao et al.

Wait-Less Offline Tuning and Re-solving for Online Decision Making

Jingruo Sun, Wenzhi Gao, Ellen Vitercik et al.

Beyond Skip Connection: Pooling and Unpooling Design for Elimination Singularities

Chengkun Sun, Jinqian Pan, Zhuoli Jin et al.

BGDB: Bernoulli-Gaussian Decision Block with Improved Denoising Diffusion Probabilistic Models

Chengkun Sun, Jinqian Pan, Russell Stevens Terry et al.

Generative Data Mining with Longtail-Guided Diffusion

David Hayden, Mao Ye, Timur Garipov et al.

Elliptic Loss Regularization

Ali Hasan, Haoming Yang, Yuting Ng et al.

Kernel Quantile Embeddings and Associated Probability Metrics

Masha Naslidnyk, Siu Lun Chau, Francois-Xavier Briol et al.

Mechanistic PDE Networks for Discovery of Governing Equations

Adeel Pervez, Efstratios Gavves, Francesco Locatello

Sampling Binary Data by Denoising through Score Functions

Francis Bach, Saeed Saremi

Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning

Sunwoo Lee, Jaebak Hwang, Yonghyeon Jo et al.

IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction

Zhangyi Hu, Jiemin Wu, Hua XU et al.

Learn How to Query from Unlabeled Data Streams in Federated Learning

Yuchang Sun, Xinran Li, Tao Lin et al.

Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning

Hui Zeng, Wenke Huang, Tongqing Zhou et al.

Semantix: An Energy-guided Sampler for Semantic Style Transfer

Huiang He, Minghui HU, Chuanxia Zheng et al.

Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence

Shayan Talaei, Matin Ansaripour, Giorgi Nadiradze et al.

Robust Root Cause Diagnosis using In-Distribution Interventions

Lokesh Nagalapatti, Ashutosh Srivastava, Sunita Sarawagi et al.

ConcreTizer: Model Inversion Attack via Occupancy Classification and Dispersion Control for 3D Point Cloud Restoration

Youngseok Kim, Sunwook Hwang, Hyung-Sin Kim et al.

Hybrid Data-Free Knowledge Distillation

Jialiang Tang, Shuo Chen, Chen Gong

VidEmo: Affective-Tree Reasoning for Emotion-Centric Video Foundation Models

Zhicheng Zhang, Weicheng Wang, Yongjie Zhu et al.

SkillTree: Explainable Skill-Based Deep Reinforcement Learning for Long-Horizon Control Tasks

Yongyan Wen, Siyuan Li, Rongchang Zuo et al.

FairICP: Encouraging Equalized Odds via Inverse Conditional Permutation

Yuheng Lai, Leying Guan

Oracle-MoE: Locality-preserving Routing in the Oracle Space for Memory-constrained Large Language Model Inference

Jixian Zhou, Fang DONG(董方), Ruijun Huang et al.

Leveraging Per-Instance Privacy for Machine Unlearning

Naz Sepahvand, Anvith Thudi, Berivan Isik et al.

A Wiener Process Perspective on Local Intrinsic Dimension Estimation Methods

Piotr Tempczyk, Łukasz Garncarek, Dominik Filipiak et al.

Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning

Yaoquan Wei, Shunyu Liu, Jie Song et al.

Learning Juntas under Markov Random Fields

Gautam Chandrasekaran, Adam Klivans

Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning

Jungtaek Kim

A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models

Shivam Kumar, Yun Yang, Lizhen Lin

Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data

Siqi Guo, Ilgee Hong, Vicente Balmaseda et al.

DynAlign: Unsupervised Dynamic Taxonomy Alignment for Cross-Domain Segmentation

HAN SUN, Rui Gong, Ismail Nejjar et al.

Positional Encoding meets Persistent Homology on Graphs

Yogesh Verma, Amauri Souza, Vikas Garg

Efficient Off-Policy Learning for High-Dimensional Action Spaces

Fabian Otto, Philipp Becker, Vien A Ngo et al.

Distributed Differentially Private Data Analytics via Secure Sketching

Jakob Burkhardt, Hannah Keller, Claudio Orlandi et al.

Asynchronous Distributed Gaussian Process Regression

Zewen Yang, Xiaobing Dai, Sandra Hirche

Constrained Pareto Set Identification with Bandit Feedback

Cyrille Kone, Emilie Kaufmann, Laura Richert

L3Ms — Lagrange Large Language Models

Guneet Singh Dhillon, Xingjian Shi, Yee Whye Teh et al.

QiMeng-SALV: Signal-Aware Learning for Verilog Code Generation

Yang Zhang, Rui Zhang, Jiaming Guo et al.

SWEb: A Large Web Dataset for the Scandinavian Languages

Tobias Norlund, Tim Isbister, Amaru Cuba Gyllensten et al.

Enhanced Denesity Peak Clustering for High-Dimensional Data

Zhongli Wang, Jie Yang, Junyi Guan et al.

Origin Identification for Text-Guided Image-to-Image Diffusion Models

Wenhao Wang, Yifan Sun, Zongxin Yang et al.

Efficient Skill Discovery via Regret-Aware Optimization

He ZHANG, Ming Zhou, shaopeng zhai et al.

Speed Master: Quick or Slow Play to Attack Speaker Recognition

Zhe Ye, Wenjie Zhang, Ying Ren et al.

Cowpox: Towards the Immunity of VLM-based Multi-Agent Systems

YUTONG WU, Jie Zhang, Yiming Li et al.

Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field Games

Antonio Ocello, Daniil Tiapkin, Lorenzo Mancini et al.

AKRMap: Adaptive Kernel Regression for Trustworthy Visualization of Cross-Modal Embeddings

Yilin Ye, Junchao Huang, Xingchen ZENG et al.

Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting

Tianyi Yin, Jingwei Wang, Yunlong Ma et al.

Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data

Erez Peterfreund, Ofir Lindenbaum, Yuval Kluger et al.

Earley-Driven Dynamic Pruning for Efficient Structured Decoding

Xintong Sun, Chi Wei, Minghao Tian et al.

Event-Driven Online Vertical Federated Learning

Ganyu Wang, Boyu Wang, Bin Gu et al.

Noisy Correspondence Rectification via Asymmetric Similarity Learning

Yunbo Wang, YuJie Wu, Zhien Dai et al.

Treasures in Discarded Weights for LLM Quantization

Hao Yu, Yang Zhou, Bohua Chen et al.

Safety Depth in Large Language Models: A Markov Chain Perspective

Ching-Chia Kao, Chia-Mu Yu, Chun-Shien Lu et al.

SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes

Yishan Shen, Yuyang Ye, Hui Xiong et al.

Scale-aware Recognition in Satellite Images under Resource Constraints

Shreelekha Revankar, Cheng Perng Phoo, Utkarsh Kumar Mall et al.

Convergence of Policy Mirror Descent Beyond Compatible Function Approximation

Uri Sherman, Tomer Koren, Yishay Mansour

Enhancing Audiovisual Speech Recognition Through Bifocal Preference Optimization

Yihan Wu, Yichen Lu, Yifan Peng et al.

TMetaNet: Topological Meta-Learning Framework for Dynamic Link Prediction

Hao Li, Hao Wan, Yuzhou Chen et al.

Class Semantic Attribute Perception Guided Zero-Shot Learning

Qin Yue, Junbiao Cui, Jianqing Liang et al.

Provable Length Generalization in Sequence Prediction via Spectral Filtering

Annie Marsden, Evan Dogariu, Naman Agarwal et al.

Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus et al.

The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws

Tian Jin, Ahmed Imtiaz Humayun, Utku Evci et al.

Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization

Zijian Liu, Zhengyuan Zhou

Learning from True-False Labels via Multi-modal Prompt Retrieving

Zhongnian Li, Jinghao Xu, Peng Ying et al.

Blend the Separated: Mixture of Synergistic Experts for Data-Scarcity Drug-Target Interaction Prediction

Xinlong Zhai, Chunchen Wang, Ruijia Wang et al.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning

Thalles Silva, Helio Pedrini, Adín Ramírez Rivera

Leveraging Predictive Equivalence in Decision Trees

Hayden McTavish, Zachery Boner, Jon Donnelly et al.

Learning Invariant Causal Mechanism from Vision-Language Models

Zeen Song, Siyu Zhao, Xingyu Zhang et al.

Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective

Yujin Oh, Pengfei Jin, Sangjoon Park et al.

Generalized Video Moment Retrieval

Qin You, Qilong Wu, Yicong Li et al.

From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models

MINGJIA YIN, Junwei Pan, Hao Wang et al.

Trajectory-Class-Aware Multi-Agent Reinforcement Learning

Hyungho Na, Kwanghyeon Lee, Sumin Lee et al.

Unveiling the Power of Multiple Gossip Steps: A Stability-Based Generalization Analysis in Decentralized Training

Multi-label Self Knowledge Distillation

Xucong Wang, Pengkun Wang, Shurui Zhang et al.

Highly Efficient Rotation-Invariant Spectral Embedding for Scalable Incomplete Multi-View Clustering

Xinxin Wang, Yongshan Zhang, Yicong Zhou

Few-Shot Knowledge Distillation of LLMs With Counterfactual Explanations

Faisal Hamman, Pasan Dissanayake, Yanjun Fu et al.

Set-Valued Sensitivity Analysis of Deep Neural Networks

Xin Wang, Feilong Wang, Xuegang (Jeff) Ban

Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos

Tianyi Zhang, Yu Cao, Dianbo Liu

ComLoRA: A Competitive Learning Approach for Enhancing LoRA

Qiushi Huang, Tom Ko, Lilian Tang et al.

LoGoFair: Post-Processing for Local and Global Fairness in Federated Learning

Li Zhang, Chaochao Chen, Zhongxuan Han et al.

Discovering Latent Causal Graphs from Spatiotemporal Data

Kun Wang, Sumanth Varambally, Duncan Watson-Parris et al.

From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection

Moritz Vandenhirtz, Julia Vogt

Unlocking the Potential of Black-box Pre-trained GNNs for Graph Few-shot Learning

Qiannan Zhang, Shichao Pei, Yuan Fang et al.

FAPEX: Fractional Amplitude-Phase Expressor for Robust Cross-Subject Seizure Prediction

Ruizhe Zheng, Lingyan Mao, DINGDING HAN et al.

Identifying and Understanding Cross-Class Features in Adversarial Training

Zeming Wei, Yiwen Guo, Yisen Wang

On the rankability of visual embeddings

Ankit Sonthalia, Arnas Uselis, Seong Joon Oh

Cross-regularization: Adaptive Model Complexity through Validation Gradients

Carlos Stein Naves de Brito

Neural Collapse Inspired Knowledge Distillation

Shuoxi Zhang, Zijian Song, Kun He

Zero-cost Proxy for Adversarial Robustness Evaluation

Yuqi Feng, Yuwei Ou, Jiahao Fan et al.

Towards Rationale-Answer Alignment of LVLMs via Self-Rationale Calibration

Yuanchen Wu, Ke Yan, Shouhong Ding et al.

Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory

Dominik Fuchsgruber, Tom Wollschläger, Johannes Bordne et al.

Centrality-guided Pre-training for Graph

Bin Liang, Shiwei Chen, Lin Gui et al.

Metric-Driven Attributions for Vision Transformers

Chase Walker, Sumit Jha, Rickard Ewetz

Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios

Hongwei Wen, Annika Betken, Hanyuan Hang

Execution-guided within-prompt search for programming-by-example

Gust Verbruggen, Ashish Tiwari, Mukul Singh et al.

Towards Macro-AUC Oriented Imbalanced Multi-Label Continual Learning

Yan Zhang, Guoqiang Wu, Bingzheng Wang et al.

Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming

Qian Li, Minghui Ouyang, Tian Ding et al.

Navigating Towards Fairness with Data Selection

Yixuan Zhang, Zhidong Li, Yang Wang et al.

Global-Semantic Alignment Distillation for Partial Multi-view Classification

Xiaoli Wang, Anqi Huang, Yongli Wang et al.

Info-Coevolution: An Efficient Framework for Data Model Coevolution

Ziheng Qin, Hailun Xu, Wei Yew et al.

Beyond single neurons: population response geometry in digital twins of mouse visual cortex

Dario Liscai, Emanuele Luconi, Alessandro Marin Vargas et al.

Efficient Reinforcement Learning Through Adaptively Pretrained Visual Encoder

Yuhan Zhang, Guoqing Ma, Guangfu Hao et al.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs

Yinong O Wang, Nivedha Sivakumar, Falaah Arif Khan et al.

Offline-to-Online Reinforcement Learning with Classifier-Free Diffusion Generation

Xiao Huang, Xu Liu, Enze Zhang et al.

Learn to Vaccinate: Combining Structure Learning and Effective Vaccination for Epidemic and Outbreak Control

Sepehr Elahi, Paula Mürmann, Patrick Thiran

Fast Estimation of Partial Dependence Functions using Trees

Jinyang Liu, Tessa Steensgaard, Marvin N. Wright et al.

Domain Adaptive Unfolded Graph Neural Networks

Zepeng Zhang, Olga Fink

Inverse decision-making using neural amortized Bayesian actors

Dominik Straub, Tobias Fabian Niehues, Jan Peters et al.

Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization

Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh et al.

Beyond Accuracy: On the Effects of Fine-Tuning Towards Vision-Language Model’s Prediction Rationality

Qitong Wang, Tang Li, Kien X. Nguyen et al.

Binary Hypothesis Testing for Softmax Models and Leverage Score Models

Yuzhou Gu, Zhao Song, Junze Yin

Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions

Canzhe Zhao, Xiangcheng Zhang, Baoxiang Wang et al.

Supervised Score-Based Modeling by Gradient Boosting

Changyuan Zhao, Hongyang Du, Guangyuan Liu et al.

Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains

Zhuo He, Shuang Li, Wenze Song et al.

Interactive Adjustment for Human Trajectory Prediction with Individual Feedback

Jianhua Sun, Yuxuan Li, Liang Chai et al.

Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates

Puning Zhao, Jiafei Wu, Zhe Liu et al.

On the Importance of Embedding Norms in Self-Supervised Learning

Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich et al.

Systems with Switching Causal Relations: A Meta-Causal Perspective

Moritz Willig, Tim Tobiasch, Florian Busch et al.

Model-Based Exploration in Monitored Markov Decision Processes

Alireza Kazemipour, Matthew Taylor, Michael Bowling

Twofold Debiasing Enhances Fine-Grained Learning with Coarse Labels

Xin-yang Zhao, Jian Jin, Yang-yang Li et al.

MeRino: Entropy-Driven Design for Generative Language Models on IoT Devices

Youpeng Zhao, Ming Lin, Huadong Tang et al.

Infinite Neural Operators: Gaussian processes on functions

Daniel Augusto de Souza, Yuchen Zhu, Jake Cunningham et al.

Towards Scalable Topological Regularizers

Wong Hiu-Tung, Darrick Lee, Hong Yan

An Asymptotically Optimal Approximation Algorithm for Multiobjective Submodular Maximization at Scale

Fabian Spaeh, Atsushi Miyauchi

Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning

Fangwen Wu, Lechao Cheng, Shengeng Tang et al.

Predicate Hierarchies Improve Few-Shot State Classification

Emily Jin, Joy Hsu, Jiajun Wu

DS-VLM: Diffusion Supervision Vision Language Model

Zhen Sun, Yunhang Shen, Jie Li et al.

Batch Selection for Multi-Label Classification Guided by Uncertainty and Dynamic Label Correlations

Ao Zhou, Bin Liu, Jin Wang et al.

Dynamic Operator Optimization for Efficient Multi-Tenant LoRA Model Serving

Changhai Zhou, Yuhua Zhou, Shiyang Zhang et al.

Pixel-level Certified Explanations via Randomized Smoothing

Alaa Anani, Tobias Lorenz, Mario Fritz et al.

On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks

Junwei Su, Chuan Wu

Action-Dependent Optimality-Preserving Reward Shaping

Grant Forbes, Jianxun Wang, Leonardo Villalobos-Arias et al.

Smooth Interpolation for Improved Discrete Graph Generative Models

Yuxuan Song, Juntong Shi, Jingjing Gong et al.

New Bounds for Sparse Variational Gaussian Processes

Michalis Titsias

Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration

Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen et al.

Improving the Effective Receptive Field of Message-Passing Neural Networks

Shahaf E. Finder, Ron Shapira Weber, Moshe Eliasof et al.

Dynamic Uncertainty Estimation for Offline Reinforcement Learning

Jiesheng Wang, Lin Li, Wei Wei et al.

Class and Attribute-Aware Logit Adjustment for Generalized Long-Tail Learning

Xiaoling Zhou, Ou Wu, Nan Yang

Generalization Bounds via Meta-Learned Model Representations: PAC-Bayes and Sample Compression Hypernetworks

Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours et al.

Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation

Junyu Luo, Yuhao Tang, Yiwei Fu et al.

Cooperative Policy Agreement: Learning Diverse Policy for Offline MARL

Yihe Zhou, Yuxuan Zheng, Yue Hu et al.

Node Similarities under Random Projections: Limits and Pathological Cases

Tvrtko Tadić, Cassiano O Becker, Jennifer Neville

Quantum Speedup for Hypergraph Sparsification

Chenghua Liu, Minbo Gao, Zhengfeng Ji et al.

When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach

Qian Chen, Lei Li, Qian Li et al.

Single-Loop Federated Actor-Critic across Heterogeneous Environments

Ye Zhu, Xiaowen Gong

A Large-scale Training Paradigm for Graph Generative Models

Yu Wang, Ryan Rossi, Namyong Park et al.

Tightening Causal Bounds via Covariate-Aware Optimal Transport

Sirui Lin, Zijun Gao, Jose Blanchet et al.

ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems

Yeqing Qiu, Ye XUE, Akang Wang et al.

Rethinking Benign Overfitting in Two-Layer Neural Networks

Ruichen Xu, Kexin Chen

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models

peijie liu, Fengli Xu, Yong Li

Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data

Xinshuai Dong, Ignavier Ng, Boyang Sun et al.

Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres

Muskan Dosi, Chiranjeev Chiranjeev, Kartik Thakral et al.

Test-Time Adaptation with Binary Feedback

Taeckyung Lee, Sorn Chottananurak, Junsu Kim et al.

Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?

Guiomar Pescador-Barrios, Sarah Filippi, Mark van der Wilk

Generating Less Certain Adversarial Examples Improves Robust Generalization

Minxing Zhang, Michael Backes, Xiao Zhang

Decoupled Finetuning for Domain Generalizable Semantic Segmentation

Jaehyun Pahk, Donghyeon Kwon, Seong Joon Oh et al.

RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks

Nazia Tasnim, Bryan Plummer

Pushing the Limits of BFP on Narrow Precision LLM Inference

Hui Wang, Yuan Cheng, Xiaomeng Han et al.

SFESS: Score Function Estimators for $k$-Subset Sampling

Klas Wijk, Ricardo Vinuesa, Hossein Azizpour

FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models

Xinting Liao, Weiming Liu, Jiaming Qian et al.

PIPA: Preference Alignment as Prior-Informed Statistical Estimation

Junbo Li, Zhangyang “Atlas” Wang, qiang liu

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills

Aidan Curtis, Eric Li, Michael S Noseworthy et al.

Variational Learning Finds Flatter Solutions at the Edge of Stability

Avrajit Ghosh, Bai Cong, Rio Yokota et al.

Learning Mean Field Control on Sparse Graphs

Christian Fabian, Kai Cui, Heinz Koeppl

Unsupervised Translation of Emergent Communication

Ido Levy, Orr Paradise, Boaz Carmeli et al.

Epistemic Bellman Operators

Pascal R. van der Vaart, Matthijs T. J. Spaan, Neil Yorke-Smith

Improving Compositional Generation with Diffusion Models Using Lift Scores

Chenning Yu, Sicun Gao

NBDI: A Simple and Effective Termination Condition for Skill Extraction from Task-Agnostic Demonstrations

Myunsoo Kim, Hayeong Lee, Seong-Woong Shim et al.

PRDP: Progressively Refined Differentiable Physics

Kanishk Bhatia, Felix Koehler, Nils Thuerey

Optimally Solving Simultaneous-Move Dec-POMDPs: The Sequential Central Planning Approach

Johan Peralez, Aurélien Delage, Jacopo Castellini et al.

Investigating Relational State Abstraction in Collaborative MARL

Sharlin Utke, Jeremie Houssineau, Giovanni Montana

Magical: Medical Lay Language Generation via Semantic Invariance and Layperson-tailored Adaptation

Weibin Liao, Tianlong Wang, Yinghao Zhu et al.

BILBO: BILevel Bayesian Optimization

Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low

A Multiagent Path Search Algorithm for Large-Scale Coalition Structure Generation

Redha Taguelmimt, Samir Aknine, Djamila Boukredera et al.

Better Understandings and Configurations in MaxSAT Stochastic Local Search Solvers via Anytime Performance Analysis

Furong Ye, Chuan Luo, Shaowei Cai

SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning

Xu Wan, Chao Yang, Cheng Yang et al.

Decoupled SGDA for Games with Intermittent Strategy Communication

Ali Zindari, Parham Yazdkhasti, Anton Rodomanov et al.

The Limits of Predicting Agents from Behaviour

Alexis Bellot, Jonathan Richens, Tom Everitt

Compositional Condition Question Answering in Tabular Understanding

Jun-Peng Jiang, Tao Zhou, De-Chuan Zhan et al.

TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning

Ron Shapira Weber, shahar benishay, Andrey Lavrinenko et al.

Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality Gap

Christopher Liao, Christian So, Theodoros Tsiligkaridis et al.

Generative Adversarial Ranking Nets

Yinghua Yao, Yuangang Pan, Jing Li et al.

Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting

Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac et al.

Learning Fused State Representations for Control from Multi-View Observations

Zeyu Wang, Yao-Hui Li, Xin Li et al.

Nonparametric Identification of Latent Concepts

Yujia Zheng, Shaoan Xie, Kun Zhang

CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution

Yunju Cho, Jay-Yoon Lee

InfoCons: Identifying Interpretable Critical Concepts in Point Clouds via Information Theory

Feifei Li, Mi Zhang, Zhaoxiang Wang et al.

MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures

Anvith Thudi, Chris Maddison

Streamline Without Sacrifice - Squeeze out Computation Redundancy in LMM

Penghao Wu, Lewei Lu, Ziwei Liu

On the Price of Differential Privacy for Hierarchical Clustering

Chengyuan Deng, Jie Gao, Jalaj Upadhyay et al.

PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models

Alex Velez-Arce, Marinka Zitnik

Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian

Thomas Paniagua, Chinmay Savadikar, Tianfu Wu

DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces

Jacob F. Pettit, Chak Shing Lee, Jiachen Yang et al.

Learning Likelihood-Free Reference Priors

Nick Bishop, Daniel Jarne Ornia, Joel Dyer et al.

Learning with Exact Invariances in Polynomial Time

Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka et al.

REM: A Scalable Reinforced Multi-Expert Framework for Multiplex Influence Maximization

Huyen Nguyen, Hieu Dam, Nguyen Hoang Khoi Do et al.

Contextures: Representations from Contexts

Runtian Zhai, Kai Yang, Burak VARICI et al.

Towards Unbiased Calibration using Meta-Regularization

Jacek Golebiowski, Cheng Wang

CSL-L2M: Controllable Song-Level Lyric-to-Melody Generation Based on Conditional Transformer with Fine-Grained Lyric and Musical Controls

Li Chai, Donglin Wang

Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra

Raphael Meyer, William Swartworth, David Woodruff

Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models

Konstantin Donhauser, Kristina Ulicna, Gemma Moran et al.