Most Cited ICML "temporal predicate prediction" Papers
5,975 papers found • Page 29 of 30
Conference
S4S: Solving for a Fast Diffusion Model Solver
Eric Frankel, Sitan Chen, Jerry Li et al.
Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization
Peiyan Zhang, Haibo Jin, Leyang Hu et al.
Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts
Jiahai Feng, Stuart Russell, Jacob Steinhardt
Uniform Mean Estimation for Heavy-Tailed Distributions via Median-of-Means
Mikael Møller Høgsgaard, Andrea Paudice
FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting
Yue Jiang, Yile Chen, Xiucheng Li et al.
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang et al.
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jimenez Gutierrez, Yiheng Shu, Weijian Qi et al.
DRAG: Data Reconstruction Attack using Guided Diffusion
Wa-Kin Lei, Jun-Cheng Chen, Shang-Tse Chen
FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation
Srijith Nair, Michael Lin, Peizhong Ju et al.
Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning
Zhiyao Zhang, Myeung Suk Oh, Hairi et al.
The Jailbreak Tax: How Useful are Your Jailbreak Outputs?
Kristina Nikolić, Luze Sun, Jie Zhang et al.
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
Chen-Xiao Gao, Chenyang Wu, Mingjun Cao et al.
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal, Sattar Vakili, Laura Toni et al.
Gridded Transformer Neural Processes for Spatio-Temporal Data
Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.
Latent Mamba Operator for Partial Differential Equations
Karn Tiwari, Niladri Dutta, N M Anoop Krishnan et al.
High-Dimensional Prediction for Sequential Decision Making
Georgy Noarov, Ramya Ramalingam, Aaron Roth et al.
Steering Protein Language Models
Long-Kai Huang, Rongyi Zhu, Bing He et al.
Cross-City Latent Space Alignment for Consistency Region Embedding
Meng Chen, Hongwei Jia, Zechen Li et al.
Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.
Diffusion Adversarial Post-Training for One-Step Video Generation
Shanchuan Lin, Xin Xia, Yuxi Ren et al.
Adaptive Sensitivity Analysis for Robust Augmentation against Natural Corruptions in Image Segmentation
Laura Zheng, Wenjie Wei, Tony Wu et al.
Closed-form Solutions: A New Perspective on Solving Differential Equations
Shu Wei, Yanjie Li, Lina Yu et al.
David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training
Weijian Luo, colin zhang, Debing Zhang et al.
A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
Zachary Roch, George Atia, Yue Wang
Statistical Test for Feature Selection Pipelines by Selective Inference
Tomohiro Shiraishi, Tatsuya Matsukawa, Shuichi Nishino et al.
Position: AI Safety should prioritize the Future of Work
Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu et al.
Geometry-Informed Neural Networks
Arturs Berzins, Andreas Radler, Eric Volkmann et al.
SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models
Yung-Sung Chuang, Benjamin Cohen-Wang, Shannon Shen et al.
Multiaccuracy and Multicalibration via Proxy Groups
Beepul Bharti, Mary Clemens-Sewall, Paul H. Yi et al.
A Model of Place Field Reorganization During Reward Maximization
M Ganesh Kumar, Blake Bordelon, Jacob A Zavatone-Veth et al.
Representative Language Generation
Charlotte Peale, Vinod Raman, Omer Reingold
Detecting Strategic Deception with Linear Probes
Nicholas Goldowsky-Dill, Bilal Chughtai, Stefan Heimersheim et al.
LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data
Peer Nagy, Sascha Frey, Kang Li et al.
Curse of High Dimensionality Issue in Transformer for Long Context Modeling
Shuhai Zhang, Zeng You, Yaofo Chen et al.
Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations
Juwei Yue, Haikuo Li, Jiawei Sheng et al.
Goal-Oriented Skill Abstraction for Offline Multi-Task Reinforcement Learning
Jinmin He, Kai Li, Yifan Zang et al.
Score-of-Mixture Training: One-Step Generative Model Training Made Simple via Score Estimation of Mixture Distributions
Tejas Jayashankar, Jongha (Jon) Ryu, Gregory Wornell
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
Firas Laakom, Haobo Chen, Jürgen Schmidhuber et al.
SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space
Xupeng Zhu, Fan Wang, Robin Walters et al.
Hypo3D: Exploring Hypothetical Reasoning in 3D
Ye Mao, Weixun Luo, Junpeng Jing et al.
Maximum Entropy Reinforcement Learning with Diffusion Policy
Xiaoyi Dong, Jian Cheng, Xi Zhang
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability
Michael Crawshaw, Blake Woodworth, Mingrui Liu
Return Capping: Sample Efficient CVaR Policy Gradient Optimisation
Harry Mead, Clarissa Costen, Bruno Lacerda et al.
Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
Yucen Li, Daohan Lu, Polina Kirichenko et al.
Sample Complexity of Distributionally Robust Off-Dynamics Reinforcement Learning with Online Interaction
Yiting He, Zhishuai Liu, Weixin Wang et al.
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
Ningyi Liao, Zihao Yu, Ruixiao Zeng et al.
Exploring Representations and Interventions in Time Series Foundation Models
Michal Wilinski, Mononito Goswami, Willa Potosnak et al.
Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers
Alireza Amiribavandpour, Xinting Huang, Mark Rofin et al.
Action Dubber: Timing Audible Actions via Inflectional Flow
Wenlong Wan, Weiying Zheng, Tianyi Xiang et al.
FLAM: Frame-Wise Language-Audio Modeling
Yusong Wu, Christos Tsirigotis, Ke Chen et al.
Robust Sparsification via Sensitivity
Chansophea Wathanak In, Yi Li, David Woodruff et al.
Rényi Neural Processes
Xuesong Wang, He Zhao, Edwin V. Bonilla
Adaptive Sample Sharing for Multi Agent Linear Bandits
Hamza Cherkaoui, Merwan Barlier, Igor Colin
Zero-Shot Offline Imitation Learning via Optimal Transport
Thomas Rupf, Marco Bagatella, Nico Gürtler et al.
Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models
Linhao Luo, Zicheng Zhao, Reza Haffari et al.
FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making
Yucen Wang, Rui Yu, Shenghua Wan et al.
Anytime-Constrained Equilibria in Polynomial Time
Jeremy McMahan
Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations
Jeet Mohapatra, Nima Dehmamy, Csaba Both et al.
Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing
Han Jiang, Xiaoyuan Yi, Zhihua Wei et al.
Telling Peer Direct Effects from Indirect Effects in Observational Network Data
Xiaojing Du, Jiuyong Li, Debo Cheng et al.
Partially Observable Reinforcement Learning with Memory Traces
Onno Eberhard, Michael Muehlebach, Claire Vernade
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
Simone Bombari, Marco Mondelli
EPIC: Efficient Position-Independent Caching for Serving Large Language Models
JUNHAO HU, Wenrui Huang, Weidong Wang et al.
Multivariate Conformal Selection
Tian Bai, Yue Zhao, Xiang Yu et al.
PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs
Jianqing Zhang, Yang Liu, Jie Fu et al.
Direct Motion Models for Assessing Generated Videos
Kelsey Allen, Carl Doersch, Guangyao Zhou et al.
How Effective Can Dropout Be in Multiple Instance Learning ?
Wenhui Zhu, Peijie Qiu, Xiwen Chen et al.
Understanding Synthetic Context Extension via Retrieval Heads
Xinyu Zhao, Fangcong Yin, Greg Durrett
KernelBench: Can LLMs Write Efficient GPU Kernels?
Anne Ouyang, Simon Guo, Simran Arora et al.
Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization
Cameron Jakub, Mihai Nica
MARS: Unleashing the Power of Variance Reduction for Training Large Models
Huizhuo Yuan, Yifeng Liu, Shuang Wu et al.
ADIOS: Antibody Development via Opponent Shaping
Sebastian Towers, Aleksandra Kalisz, Philippe Robert et al.
Reinforcement Learning for Quantum Control under Physical Constraints
Jan Ole Ernst, Aniket Chatterjee, Tim Franzmeyer et al.
Automated Benchmark Generation for Repository-Level Coding Tasks
Konstantinos Vergopoulos, Mark Müller, Martin Vechev
Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models
Yinhong Liu, Zhijiang Guo, Tianya Liang et al.
Attention-Level Speculation
Jack Cai, Ammar Vora, Randolph Zhang et al.
Unified Screening for Multiple Diseases
Yiğit Narter, Alihan Hüyük, Mihaela van der Schaar et al.
Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly From Data
Krzysztof Kacprzyk, Julianna Piskorz, Mihaela van der Schaar
Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Elucidating the Design Space of Multimodal Protein Language Models
Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang et al.
Models of Heavy-Tailed Mechanistic Universality
Liam Hodgkinson, Zhichao Wang, Michael Mahoney
Stochastic Encodings for Active Feature Acquisition
Alexander Norcliffe, Changhee Lee, Fergus Imrie et al.
Sum-of-Parts: Self-Attributing Neural Networks with End-to-End Learning of Feature Groups
Weiqiu You, Helen Qu, Marco Gatti et al.
Balancing Preservation and Modification: A Region and Semantic Aware Metric for Instruction-Based Image Editing
Zhuoying Li, Zhu Xu, Yuxin Peng et al.
On the Similarities of Embeddings in Contrastive Learning
Chungpa Lee, Sehee Lim, Kibok Lee et al.
Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
Zhenglin Wan, Xingrui Yu, David Bossens et al.
MedRAX: Medical Reasoning Agent for Chest X-ray
Adibvafa Fallahpour, Jun Ma, Alif Munim et al.
Time Series Representations with Hard-Coded Invariances
Thibaut Germain, Chrysoula Kosma, Laurent Oudre
High-Fidelity Simultaneous Speech-To-Speech Translation
Tom Labiausse, Laurent Mazaré, Edouard Grave et al.
Taming Diffusion for Dataset Distillation with High Representativeness
Lin Zhao, Yushu Wu, Xinru Jiang et al.
Symmetry-Robust 3D Orientation Estimation
Christopher Scarvelis, David Benhaim, Paul Zhang
PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning
Angel Villar-Corrales, Sven Behnke
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci et al.
World Model Implanting for Test-time Adaptation of Embodied Agents
Minjong Yoo, Jinwoo Jang, Sihyung Yoon et al.
Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods
Yedi Zhang, Yufan Cai, Xinyue Zuo et al.
Position: Strong Consumer Protection is an Inalienable Defense for AI Safety in the United States
Serena Booth
Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus Kirkman, Graham Todd et al.
Position: The Categorization of Race in ML is a Flawed Premise
Miriam Doh, Benedikt Höltgen, Piera Riccio et al.
Position: Not All Explanations for Deep Learning Phenomena Are Equally Valuable
Alan Jeffares, Mihaela van der Schaar
M³HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
Ziyan Wang, Zhicheng Zhang, Fei Fang et al.
Parametric Scaling Law of Tuning Bias in Conformal Prediction
Hao Zeng, Kangdao Liu, Bingyi Jing et al.
Position: General Intelligence Requires Reward-based Pretraining
Seungwook Han, Jyothish Pari, Samuel Gershman et al.
Position: AI Evaluation Should Learn from How We Test Humans
Yan Zhuang, Qi Liu, Zachary Pardos et al.
Position: Uncertainty Quantification Needs Reassessment for Large Language Model Agents
Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci
Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived
Yuhe Guo, Huayi Tang, Jiahong Ma et al.
Position: Formal Mathematical Reasoning—A New Frontier in AI
Kaiyu Yang, Gabriel Poesia, Jingxuan He et al.
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research
Patrik Reizinger, Randall Balestriero, David Klindt et al.
Joint Localization and Activation Editing for Low-Resource Fine-Tuning
Wen Lai, Alexander Fraser, Ivan Titov
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
Ossi Räisä, Boris van Breugel, Mihaela van der Schaar
Position: Theory of Mind Benchmarks are Broken for Large Language Models
Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf et al.
Position: Explainable AI Cannot Advance Without Better User Studies
Matej Pičulin, Bernarda Petek, Irena Ograjenšek et al.
Position: When Incentives Backfire, Data Stops Being Human
Sebastin Santy, Prasanta Bhattacharya, Manoel Ribeiro et al.
Position: Constants are Critical in Regret Bounds for Reinforcement Learning
Simone Drago, Marco Mussi, Alberto Maria Metelli
Continuous Bayesian Model Selection for Multivariate Causal Discovery
Anish Dhir, Ruby Sedgwick, Avinash Kori et al.
Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation
Mohit Pandey, Gopeshh Subbaraj, Artem Cherkasov et al.
Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li et al.
Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models
Mingi Jung, Saehyung Lee, Eunji Kim et al.
Text-to-LoRA: Instant Transformer Adaption
Rujikorn Charakorn, Edoardo Cetin, Yujin Tang et al.
QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval
Jaehyun Kwak, Izaaz Inhar, Se-Young Yun et al.
On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning
Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li
Let LLM Tell What to Prune and How Much to Prune
Mingzhe Yang, Sihao Lin, Changlin Li et al.
RepoAudit: An Autonomous LLM-Agent for Repository-Level Code Auditing
Jinyao Guo, Chengpeng Wang, Xiangzhe Xu et al.
Can Large Language Models Understand Intermediate Representations in Compilers?
Hailong Jiang, Jianfeng Zhu, Yao Wan et al.
Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation
Mingyu Kang, Yong Suk Choi
Learnware Specification via Dual Alignment
Wei Chen, Jun-Xiang Mao, Xiaozheng Wang et al.
On the Importance of Gaussianizing Representations
Daniel Eftekhari, Vardan Papyan
From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms
Jessica Dai, Paula Gradu, Inioluwa Raji et al.
TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization
Haowen Ma, Zhiguo Long, Hua Meng
CodeSync: Synchronizing Large Language Models with Dynamic Code Evolution at Scale
Chenlong Wang, Zhaoyang Chu, Zhengxiang Cheng et al.
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Mengyang Sun, Yihao Wang, Tao Feng et al.
Approximate Differential Privacy of the $\ell_2$ Mechanism
Matthew Joseph, Alex Kulesza, Alexander Yu
NEAR: Neural Electromagnetic Array Response
Yinyan Bu, Jiajie Yu, Kai Zheng et al.
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
Jingyang Ke, Feiyang Wu, Jiyi Wang et al.
Adversarial Inception Backdoor Attacks against Reinforcement Learning
Ethan Rathbun, Alina Oprea, Christopher Amato
Representation Preserving Multiclass Agnostic to Realizable Reduction
Steve Hanneke, Qinglin Meng, Amirreza Shaeiri
Diffusion Sampling Correction via Approximately 10 Parameters
Guangyi Wang, Wei Peng, lijiang Li et al.
Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective
Aojun Lu, Hangjie Yuan, Tao Feng et al.
Learning with Expected Signatures: Theory and Applications
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs
Hancheng Min, Rene Vidal
The underlying structures of self-attention: symmetry, directionality, and emergent dynamics in Transformer training
Matteo Saponati, Pascal J. Sager, Pau Vilimelis Aceituno et al.
Novelty Detection in Reinforcement Learning with World Models
Geigh Zollicoffer, Kenneth Eaton, Jonathan Balloch et al.
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion
Anle Ke, Xu Zhang, Tong Chen et al.
Robust Spatio-Temporal Centralized Interaction for OOD Learning
Jiaming Ma, Binwu Wang, Pengkun Wang et al.
Continuous Semi-Implicit Models
Longlin Yu, Jiajun Zha, Tong Yang et al.
Relational Invariant Learning for Robust Solvation Free Energy Prediction
Yeyun Chen
Nonlinear transformers can perform inference-time feature learning
Naoki Nishikawa, Yujin Song, Kazusato Oko et al.
Unconstrained Robust Online Convex Optimization
Jiujia Zhang, Ashok Cutkosky
On the Adversarial Robustness of Multi-Kernel Clustering
Hao Yu, Weixuan Liang, KE LIANG et al.
Phase transitions for the existence of unregularized M-estimators in single index models
Takuya Koriyama, Pierre C Bellec
Do Bayesian Neural Networks Actually Behave Like Bayesian Models?
Gábor Pituk, Vik Shirvaikar, Tom Rainforth
From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
Chi Zhang, REN Lianhai, Jingpu Cheng et al.
Competitively Consistent Clustering
Niv Buchbinder, Roie Levin, Yue Yang
Safety-Polarized and Prioritized Reinforcement Learning
Ke Fan, Jinpeng Zhang, Xuefeng Zhang et al.
Sparse Autoencoders, Again?
Yin Lu, Xuening Zhu, Tong He et al.
Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective
Lele Fu, Bowen Deng, Sheng Huang et al.
Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification
Eric Zhao, Pranjal Awasthi, Sreenivas Gollapudi
Rethinking Addressing in Language Models via Contextualized Equivariant Positional Encoding
Jiajun Zhu, Peihao Wang, Ruisi Cai et al.
Bayesian Active Learning for Bivariate Causal Discovery
Yuxuan Wang, Mingzhou Liu, Xinwei Sun et al.
How Expressive are Knowledge Graph Foundation Models?
Xingyue Huang, Pablo Barcelo, Michael Bronstein et al.
Ensemble Distribution Distillation via Flow Matching
Jonggeon Park, Giung Nam, Hyunsu Kim et al.
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal et al.
CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation
Aditya Gorla, Ryan Wang, Zhengtong Liu et al.
The Hidden Dimensions of LLM Alignment: A Multi-Dimensional Analysis of Orthogonal Safety Directions
Wenbo Pan, Zhichao Liu, Qiguang Chen et al.
Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion
Binchi Zhang, Zaiyi Zheng, Zhengzhang Chen et al.
Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
Ulzee An, Moonseong Jeong, Simon Lee et al.
Outlier-Aware Post-Training Quantization for Discrete Graph Diffusion Models
Zheng Gong, Ying Sun
ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Zhou Jie et al.
MTL-UE: Learning to Learn Nothing for Multi-Task Learning
Yi Yu, Song Xia, SIYUAN YANG et al.
Causal Attribution Analysis for Continuous Outcomes
Shanshan Luo, Yu yixuan, Chunchen LIU et al.
Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection
Louis Béthune, David Grangier, Dan Busbridge et al.
On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms
Ekaterina Borodich, Alexander Gasnikov, Dmitry Kovalev
Relative Error Fair Clustering in the Weak-Strong Oracle Model
Vladimir Braverman, Prathamesh Dharangutte, Shaofeng Jiang et al.
Doubly Protected Estimation for Survival Outcomes Utilizing External Controls for Randomized Clinical Trials
Chenyin Gao, Shu Yang, Mingyang Shan et al.
Adversarial Robustness via Deformable Convolution with Stochasticity
Yanxiang Ma, Zixuan Huang, Minjing Dong et al.
Understanding the Unfairness in Network Quantization
Bing Liu, wenjun Miao, Boyu Zhang et al.
SEAD: Unsupervised Ensemble of Streaming Anomaly Detectors
Saumya Gaurang Shah, Abishek Sankararaman, Balakrishnan Narayanaswamy et al.
Improved Lower Bounds for First-order Stochastic Non-convex Optimization under Markov Sampling
Zhenyu Sun, Ermin Wei
Latent Variable Estimation in Bayesian Black-Litterman Models
Thomas Y.L. Lin, Jerry Yao-Chieh Hu, Wan-Jiun Paul Chiou et al.
Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models
Anshuman Chhabra, Bo Li, Jian Chen et al.
BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation
Lian Liu, Xiandong Zhao, Guanchen Li et al.
Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning
Ze'ev Zukerman, Bassel Hamoud, Kfir Levy
Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax Optimization
Zhangyi Liu, Feng Liu, Rui Gao et al.
Geometric Contact Flows: Contactomorphisms for Dynamics and Control
Andrea Testa, Søren Hauberg, Tamim Asfour et al.
Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity
Ningyuan Huang, Miguel Sarabia, Abhinav Moudgil et al.
A-PSRO: A Unified Strategy Learning Method with Advantage Metric for Normal-form Games
Yudong Hu, Haoran Li, Congying Han et al.
In-Context Fine-Tuning for Time-Series Foundation Models
Matthew Faw, Rajat Sen, Yichen Zhou et al.
Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization
Guy Kornowski, Daogao Liu, Kunal Talwar
Peri-LN: Revisiting Normalization Layer in the Transformer Architecture
Jeonghoon Kim, Byeongchan Lee, Cheonbok Park et al.
High-Dimensional Tensor Regression With Oracle Properties
Wenbin Wang, Yu Shi, Ziping Zhao
FourierMamba: Fourier Learning Integration with State Space Models for Image Deraining
Dong Li, Yidi Liu, Xueyang Fu et al.
Neural Genetic Search in Discrete Spaces
Hyeonah Kim, Sanghyeok Choi, Jiwoo Son et al.
Sparse Video-Gen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity
Haocheng Xi, Shuo Yang, Yilong Zhao et al.
Discovering a Zero (Zero-Vector Class of Machine Learning)
Harikrishna Metta, Venkatesh Babu Radhakrishnan
PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities
Daniel Zilberg, Ron Levie
Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models
Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin et al.
Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization
Xiuyuan Wang, Chaochao Chen, Weiming Liu et al.
Analytical Lyapunov Function Discovery: An RL-based Generative Approach
Haohan Zou, Jie Feng, Hao Zhao et al.
T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling
Zhenyu Hou, Xin Lv, Rui Lu et al.