Most Cited ICML "semi-parametric agent" Papers
5,975 papers found • Page 16 of 30
Conference
Fast Co-Training under Weak Dependence via Stream-Based Active Learning
Ilias Diakonikolas, Mingchen Ma, Lisheng Ren et al.
Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning
Charles Dickens, Changyu Gao, Connor Pryor et al.
Efficient Algorithms for Sum-Of-Minimum Optimization
Lisang Ding, Ziang Chen, Xinshang Wang et al.
Robust Stable Spiking Neural Networks
Ding Jianhao, Zhiyu Pan, Yujia Liu et al.
Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization
Li Ding, Jenny Zhang, Jeff Clune et al.
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Yiran Ding, Li Lyna Zhang, Chengruidong Zhang et al.
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
Daniel Dodd, Louis Sharrock, Chris Nemeth
Consistent Adversarially Robust Linear Classification: Non-Parametric Setting
Elvis Dohmatob
Precise Accuracy / Robustness Tradeoffs in Regression: Case of General Norms
Elvis Dohmatob, Meyer Scetbon
Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
Nikita Doikov, Sebastian Stich, Martin Jaggi
Impact of Decentralized Learning on Player Utilities in Stackelberg Games
Kate Donahue, Nicole Immorlica, Meena Jagadeesan et al.
Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective
Yuxin Dong, Tieliang Gong, Hong Chen et al.
Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models
Peijie Dong, Lujun Li, Zhenheng Tang et al.
Position: Building Guardrails for Large Language Models Requires Systematic Design
Yi DONG, Ronghui Mu, Gaojie Jin et al.
Accelerating PDE Data Generation via Differential Operator Action in Solution Space
huanshuo dong, Hong Wang, Haoyang Liu et al.
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
Jiaxiang Dong, Haixu Wu, Yuxuan Wang et al.
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference
Harry Dong, Xinyu Yang, Zhenyu Zhang et al.
Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent
Konstantin Donhauser, Javier Abad, Neha Hulkund et al.
Spike Distance Function as a Learning Objective for Spike Prediction
Kevin Doran, Marvin Seifert, Carola Yovanovich et al.
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows
Felix Draxler, Stefan Wahl, Christoph Schnörr et al.
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
Alexandre Drouin, Maxime Gasse, Massimo Caccia et al.
Principled Gradient-Based MCMC for Conditional Sampling of Text
Li Du, Afra Amini, Lucas Torroba Hennigen et al.
Position: Compositional Generative Modeling: A Single Model is Not All You Need
Yilun Du, Leslie Kaelbling
Improving Factuality and Reasoning in Language Models through Multiagent Debate
Yilun Du, Shuang Li, Antonio Torralba et al.
Learning Iterative Reasoning through Energy Diffusion
Yilun Du, Jiayuan Mao, Josh Tenenbaum
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
YU DU, Fangyun Wei, Hongyang Zhang
MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving
Jiangfei Duan, Runyu Lu, Haojie Duanmu et al.
MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series
Jufang Duan, Wei Zheng, Yangzhou Du et al.
DE-COP: Detecting Copyrighted Content in Language Models Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
Unveiling the Potential of AI for Nanomaterial Morphology Prediction
Ivan Dubrovsky, Andrei Dmitrenko, Aleksey Dmitrenko et al.
Sharpness-Aware Data Generation for Zero-shot Quantization
Hoang Dung, Cuong Pham, Trung Le et al.
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
Max Dupre la Tour, Monika Henzinger, David Saulpic
Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation
Benjamin Dupuis, Umut Simsekli
Outlier-robust Kalman Filtering through Generalised Bayes
Gerardo Duran-Martin, Matias Altamirano, Alex Shestopaloff et al.
Barrier Algorithms for Constrained Non-Convex Optimization
Pavel Dvurechenskii, Mathias Staudigl
Equivariant Frames and the Impossibility of Continuous Canonicalization
Nadav Dym, Hannah Lawrence, Jonathan Siegel
Position: Insights from Survey Methodology can Improve Training Data
Stephanie Eckman, Barbara Plank, Frauke Kreuter
Efficient Error Certification for Physics-Informed Neural Networks
Francisco Eiras, Adel Bibi, Rudy Bunel et al.
Scalable Pre-training of Large Autoregressive Image Models
Alaaeldin Ali, Michal Klein, Shuangfei Zhai et al.
TSLANet: Rethinking Transformers for Time Series Representation Learning
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen et al.
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
Mohamed Elsayed, Homayoon Farrahi, Felix Dangel et al.
Approximate Nearest Neighbor Search with Window Filters
Josh Engels, Ben Landrum, Shangdi Yu et al.
DsDm: Model-Aware Dataset Selection with Datamodels
Logan Engstrom
Compositional Curvature Bounds for Deep Neural Networks
Taha Entesari, Sina Sharifi, Mahyar Fazlyab
PAC-Bayesian Error Bound, via Rényi Divergence, for a Class of Linear Time-Invariant State-Space Models
Deividas Eringis, john leth, Zheng-Hua Tan et al.
Model Alignment as Prospect Theoretic Optimization
Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff et al.
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
Benjamin Eyre, Elliot Creager, David Madras et al.
Revisit the Essence of Distilling Knowledge through Calibration
Wen-Shu Fan, Su Lu, Xin-Chun Li et al.
DOGE: Domain Reweighting with Generalization Estimation
Simin Fan, Matteo Pagliardini, Martin Jaggi
Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
Luyang Fang, Yongkai Chen, Wenxuan Zhong et al.
Exploring Correlations of Self-Supervised Tasks for Graphs
Taoran Fang, Wei Chow, Yifei Sun et al.
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
Han Fang, Zhihao Song, Paul Weng et al.
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Jesse Farebrother, Jordi Orbay, Quan Vuong et al.
From Geometry to Causality- Ricci Curvature and the Reliability of Causal Inference on Networks
Amirhossein Farzam, Allen Tannenbaum, Guillermo Sapiro
Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition
Hao Fei, Shengqiong Wu, Wei Ji et al.
Resisting Stochastic Risks in Diffusion Planners with the Trajectory Aggregation Tree
Lang Feng, Pengjie Gu, Bo An et al.
Fast White-Box Adversarial Streaming Without a Random Oracle
Ying Feng, Aayush Jain, David Woodruff
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao et al.
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs
Kaituo Feng, Changsheng Li, Xiaolu Zhang et al.
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Shikun Feng, Yuyan Ni, Li et al.
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates
Rémi Leluc, Aymeric Dieuleveut, François Portier et al.
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
Shanglun Feng, Florian Tramer
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
Songtao Feng, Ming Yin, Yu-Xiang Wang et al.
Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
Thomas Ferté, Dutartre Dan, Boris Hejblum et al.
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
Matthias Fey, Weihua Hu, Kexin Huang et al.
Critical feature learning in deep neural networks
Kirsten Fischer, Javed Lindner, David Dahmen et al.
Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields
Tom Fischer, Pascal Peter, Joachim Weickert et al.
Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
Aaron Fisher
Explaining Probabilistic Models with Distributional Values
Luca Franceschi, Michele Donini, Cedric Archambeau et al.
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift
Luca Franco, Paolo Mandica, Konstantinos Kallidromitis et al.
Weisfeiler-Leman at the margin: When more expressivity matters
Billy Franks, Christopher Morris, Ameya Velingker et al.
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
Kevin Frans, Seohong Park, Pieter Abbeel et al.
Trust the Model Where It Trusts Itself - Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption
Bernd Frauenknecht, Artur Eisele, Devdutt Subhasish et al.
Trustworthy Actionable Perturbations
Jesse Friedbaum, Sudarshan Adiga, Ravi Tandon
Interpretability Illusions in the Generalization of Simplified Models
Dan Friedman, Andrew Lampinen, Lucas Dixon et al.
Hyperbolic Geometric Latent Diffusion Model for Graph Generation
Xingcheng Fu, Yisen Gao, Yuecen Wei et al.
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin et al.
PinNet: Pinpoint Instructive Information for Retrieval Augmented Code-to-Text Generation
Han Fu, Jian Tan, Pinhan Zhang et al.
Towards Theoretical Understandings of Self-Consuming Generative Models
Shi Fu, Sen Zhang, Yingjie Wang et al.
Positive Concave Deep Equilibrium Models
Mateusz Gabor, Tomasz Piotrowski, Renato L. G. Cavalcante
Let Go of Your Labels with Unsupervised Transfer
Artyom Gadetsky, Yulun Jiang, Maria Brbic
Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
Kai Gan, Tong Wei
Reflective Policy Optimization
Yaozhong Gan, yan renye, zhe wu et al.
Testing the Feasibility of Linear Programs with Bandit Feedback
Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama et al.
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
Hongchang Gao
Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
Wenzhi Gao, Qi Deng
A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
Zhangyang Gao, Daize Dong, Cheng Tan et al.
Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
Riqiang Gao, Florin-Cristian Ghesu, Simon Arberet et al.
DMTG: One-Shot Differentiable Multi-Task Grouping
Yuan Gao, Shuguo Jiang, Moran Li et al.
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion
Bowen Gao, Minsi Ren, Yuyan Ni et al.
Non-convex Stochastic Composite Optimization with Polyak Momentum
Yuan Gao, Anton Rodomanov, Sebastian Stich
Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations
Feng Gao, Liangzhi Shi, Shenao Zhang et al.
Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
Wenzhi Gao, Chunlin Sun, Chenyu Xue et al.
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
Ziqi Gao, Qichao Wang, Aochuan Chen et al.
Fast-Slow Test-Time Adaptation for Online Vision-and-Language Navigation
JUNYU GAO, Xuan Yao, Changsheng Xu
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
Chenyin Gao, ZHIMING ZHANG, Shu Yang
Projection-Free Online Convex Optimization with Time-Varying Constraints
Dan Garber, Ben Kretzu
LLark: A Multimodal Instruction-Following Language Model for Music
Josh Gardner, Simon Durand, Daniel Stoller et al.
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
Bruno Gavranović, Paul Lessard, Andrew Dudzik et al.
Safe and Robust Subgame Exploitation in Imperfect Information Games
Zhenxing Ge, Zheng Xu, Tianyu Ding et al.
Don't trust your eyes: on the (un)reliability of feature visualizations
Robert Geirhos, Roland S. Zimmermann, Blair Bilodeau et al.
Learning with 3D rotations, a hitchhiker's guide to SO(3)
Andreas René Geist, Jonas Frey, Mikel Zhobro et al.
Graph-Triggered Rising Bandits
Gianmarco Genalti, Marco Mussi, Nicola Gatti et al.
Reinforcement Learning within Tree Search for Fast Macro Placement
Zijie Geng, Jie Wang, Ziyan Liu et al.
Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models
Asma Ghandeharioun, Avi Caciularu, Adam Pearce et al.
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar et al.
State-Constrained Zero-Sum Differential Games with One-Sided Information
Mukesh Ghimire, Lei Zhang, Zhe Xu et al.
Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms
Avishek Ghosh, Arya Mazumdar
Optimal Eye Surgeon: Finding image priors through sparse generators at initialization
Avrajit Ghosh, Xitong Zhang, Kenneth Sun et al.
Self-Correcting Self-Consuming Loops for Generative Model Training
Nate Gillman, Michael Freeman, Daksh Aggarwal et al.
CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
JUNCHAO GONG, LEI BAI, Peng Ye et al.
Does Label Smoothing Help Deep Partial Label Learning?
Xiuwen Gong, Nitin Bisht, Guandong Xu
AST-T5: Structure-Aware Pretraining for Code Generation and Understanding
Linyuan Gong, Mostafa Elhoushi, Alvin Cheung
Evolution-Inspired Loss Functions for Protein Representation Learning
Chengyue Gong, Adam Klivans, James Loy et al.
Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks
Linyuan Gong, Sida Wang, Mostafa Elhoushi et al.
E$^2$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation
Yifan Gong, Zheng Zhan, Qing Jin et al.
Long Range Propagation on Continuous-Time Dynamic Graphs
Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio et al.
Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates
Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo
Fine-grained Classes and How to Find Them
Matej Grcic, Artyom Gadetsky, Maria Brbic
AI Control: Improving Safety Despite Intentional Subversion
Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan et al.
Scaling Down Deep Learning with MNIST-1D
Sam Greydanus, Dmitry Kobak
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
Sebastian Gregor Gruber, Florian Buettner
EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization
Zhibin Gu, Zhendong Li, Songhe Feng
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Alex Gu, Baptiste Roziere, Hugh Leather et al.
Predictive Performance Comparison of Decision Policies Under Confounding
Luke Guerdan, Amanda Coston, Ken Holstein et al.
On the Diminishing Returns of Width for Continual Learning
Etash Guha, Vihan Lakshman
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation
Gauthier Guinet, Behrooz Tehrani, Anoop Deoras et al.
DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
Siyuan Guo, Cheng Deng, Ying Wen et al.
Collaborative Heterogeneous Causal Inference Beyond Meta-analysis
Tianyu Guo, Sai Praneeth Karimireddy, Michael Jordan
ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation
Ziao Guo, Yang Li, Chang Liu et al.
FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering
Yongxin Guo, Xiaoying Tang, Tao Lin
Compressing Large Language Models by Joint Sparsification and Quantization
Jinyang Guo, Jianyu Wu, Zining Wang et al.
Automated Loss function Search for Class-imbalanced Node Classification
Xinyu Guo, KAI WU, Xiaoyu Zhang et al.
Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
Zijian Guo, Weichao Zhou, Wenchao Li
GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks
Shivanshu Gupta, Clemens Rosenbaum, Ethan R. Elenberg
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
Jan Hagnberger, Marimuthu Kalimuthu, Daniel Musekamp et al.
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
Jaehoon Hahm, Junho Lee, Sunghyun Kim et al.
Pursuing Overall Welfare in Federated Learning through Sequential Decision Making
Seok-Ju Hahn, Gi-Soo Kim, Junghye Lee
Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming
Hany Hamed, Subin Kim, Dongyeong Kim et al.
Riemannian coordinate descent algorithms on matrix manifolds
Andi Han, Pratik Kumar Jawanpuria, Bamdev Mishra
Prototypical Transformer As Unified Motion Learners
Cheng Han, Yawen Lu, Guohao Sun et al.
SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting
Lu Han, Han-Jia Ye, De-Chuan Zhan
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
Sungwon Han, Jinsung Yoon, Sercan Arik et al.
Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning
Jun-Yi Hang, Min-Ling Zhang
MGit: A Model Versioning and Management System
Wei Hao, Daniel Mendoza, Rafael Mendes et al.
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training
Zhongkai Hao, Chang Su, LIU SONGMING et al.
Convergence Guarantees for the DeepWalk Embedding on Block Models
Christopher Harker, Aditya Bhaskara
Estimating the Permanent by Nesting Importance Sampling
Juha Harviainen, Mikko Koivisto
Position: $C^*$-Algebraic Machine Learning $-$ Moving in a New Direction
Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer
Doron Haviv, Russell Kunes, Thomas Dougherty et al.
GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements
Alexander Havrilla, Sharath Chandra Raparthy, Christoforos Nalmpantis et al.
MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation
Alexandre Hayderi, Amin Saberi, Ellen Vitercik et al.
LoRA+: Efficient Low Rank Adaptation of Large Models
Soufiane Hayou, Nikhil Ghosh, Bin Yu
Deep Neural Room Acoustics Primitive
Yuhang He, Anoop Cherian, Gordon Wichern et al.
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation
Zhenyu He, Guhao Feng, Shengjie Luo et al.
ReDiffuser: Reliable Decision-Making Using a Diffuser with Confidence Estimation
Nantian He, Shaohui Li, Zhi Li et al.
Domain-wise Data Acquisition to Improve Performance under Distribution Shift
Yue He, Dongbai Li, Pengfei Tian et al.
Quantum Algorithm for Online Exp-concave Optimization
Jianhao He, Chengchang Liu, Xutong Liu et al.
Riemannian Accelerated Zeroth-order Algorithm: Improved Robustness and Lower Query Complexity
Chang He, Zhaoye Pan, Xiao Wang et al.
Ambiguity-Aware Abductive Learning
Hao-Yuan He, Hui Sun, Zheng Xie et al.
Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning
Zhiyuan He, Yijun Yang, Pin-Yu Chen et al.
Robust Multi-Task Learning with Excess Risks
Yifei He, Shiji Zhou, Guojun Zhang et al.
DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
Kaibo He, Chenhui Zuo, Chengtian Ma et al.
Learning Useful Representations of Recurrent Neural Network Weight Matrices
Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber
Randomized Confidence Bounds for Stochastic Partial Monitoring
Maxime Heuillet, Ola Ahmad, Audrey Durand
Understanding Diffusion Models by Feynman's Path Integral
Yuji Hirono, Akinori Tanaka, Kenji Fukushima
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
Minh Hoang, Azza Fadhel, Aryan Deshwal et al.
Estimating Unknown Population Sizes Using the Hypergeometric Distribution
Liam Hodgson, Danilo Bzdok
Two Tales of Single-Phase Contrastive Hebbian Learning
Rasmus Kjær Høier, Christopher Zach
Verifying message-passing neural networks via topology-based bounds tightening
Christopher Hojny, Shiqiang Zhang, Juan Campos et al.
Criterion Collapse and Loss Distribution Control
Matthew J. Holland
Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
Floris Holstege, Bram Wouters, Noud van Giersbergen et al.
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
Junyuan Hong, Jinhao Duan, Chenhui Zhang et al.
Enhancing Sufficient Dimension Reduction via Hellinger Correlation
Seungbeom Hong, Ilmun Kim, Jun Song
A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs
Kihyuk Hong, Ambuj Tewari
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates
Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis et al.
Graph Neural PDE Solvers with Conservation and Similarity-Equivariance
Masanobu Horie, NAOTO MITSUME
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition
Samuel Horváth, Stefanos Laskaridis, Shashank Rajput et al.
Equilibrium of Data Markets with Externality
Safwan Hossain, Yiling Chen
Multi-Sender Persuasion: A Computational Perspective
Safwan Hossain, Tonghan Wang, Tao Lin et al.
IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency
Linshan Hou, Ruili Feng, Zhongyun Hua et al.
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
Charlie Hou, Akshat Shrivastava, Hongyuan Zhan et al.
Loss Shaping Constraints for Long-Term Time Series Forecasting
Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro
Careful with that Scalpel: Improving Gradient Surgery with an EMA
Yu-Guan Hsieh, James Thornton, Eugene Ndiaye et al.
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
Kyle Hsu, Jubayer Ibn Hamid, Kaylee Burns et al.
Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning
Yusong Hu, De Cheng, Dingwen Zhang et al.
An Information Theoretic Approach to Interaction-Grounded Learning
Xiaoyan Hu, Farzan Farnia, Ho-fung Leung
SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code
ziniu hu, Ahmet Iscen, Aashi Jain et al.
Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation
Dapeng Hu, Jian Liang, Xinchao Wang et al.
Improving Interpretation Faithfulness for Vision Transformers
Lijie Hu, Yixin Liu, Ninghao Liu et al.
Multigroup Robustness
Lunjia Hu, Charlotte Peale, Judy Hanwen Shen
Provable Privacy with Non-Private Pre-Processing
Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf
Case-Based or Rule-Based: How Do Transformers Do the Math?
Yi Hu, Xiaojuan Tang, Haotong Yang et al.
Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications
Zixuan Hu, Yongxian Wei, Li Shen et al.
High-Performance Temporal Reversible Spiking Neural Networks with $\mathcal{O}(L)$ Training Memory and $\mathcal{O}(1)$ Inference Cost
JiaKui Hu, Man Yao, Xuerui Qiu et al.
Accelerating Transformer Pre-training with 2:4 Sparsity
Yuezhou Hu, Kang Zhao, Weiyu Huang et al.
InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks
Xueyu Hu, Ziyu Zhao, Shuang Wei et al.
ReconBoost: Boosting Can Achieve Modality Reconcilement
Cong Hua, Qianqian Xu, Shilong Bao et al.
Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games
Kexin Huang, Ziqian Chen, xue wang et al.