ICML Poster Papers
5,104 papers found • Page 4 of 103
An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data
Nikita Lagrange, Herve Isambert
An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability
Daiqing Wu, Dongbao Yang, Sicheng Zhao et al.
An End-to-End Model for Logits-Based Large Language Models Watermarking
KA HIM WONG, Jicheng Zhou, Jiantao Zhou et al.
An Entropy-Based Model for Hierarchical Learning
Amir R. Asadi
A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability
Pouria Fatemi, Ehsan Sharifian, Mohammad Hossein Yassaee
A New Concentration Inequality for Sampling Without Replacement and Its Application for Transductive Learning
Yingzhen Yang
An Expressive and Self-Adaptive Dynamical System for Efficient Function Learning
Chuan Liu, Chunshu Wu, Ruibing Song et al.
Angle Domain Guidance: Latent Diffusion Requires Rotation Rather Than Extrapolation
Cheng Jin, Zhenyu Xiao, Chutao Liu et al.
An in depth look at the Procrustes-Wasserstein distance: properties and barycenters
Davide Adamo, Marco Corneli, Manon Vuillien et al.
An Instrumental Value for Data Production and its Application to Data Pricing
Rui Ai, Boxiang Lyu, Zhaoran Wang et al.
An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks
Valentyn Boreiko, Alexander Panfilov, Václav Voráček et al.
Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
Dongze Wu, Yao Xie
A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations
Junwei Su, Chuan Wu
A Non-isotropic Time Series Diffusion Model with Moving Average Transitions
Chenxi Wang, Linxiao Yang, Zhixian Wang et al.
An Online Learning Approach to Prompt-based Selection of Generative Models and LLMs
Xiaoyan Hu, Ho-fung Leung, Farzan Farnia
An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints
Jiahui Zhu, Kihyun Yu, Dabeen Lee et al.
A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators
Han Zhou, dr. Jordy Van Landeghem, Teodora Popordanoska et al.
Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning Attack
Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi et al.
any4: Learned 4-bit Numeric Representation for LLMs
Mostafa Elhoushi, Jeff Johnson
AnyEdit: Edit Any Knowledge Encoded in Language Models
Houcheng Jiang, Junfeng Fang, Ningyu Zhang et al.
Anytime-Constrained Equilibria in Polynomial Time
Jeremy McMahan
A Online Statistical Framework for Out-of-Distribution Detection
Xinsong Ma, Xin Zou, Weiwei Liu
A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization
Kunjie Ren, Luo Luo
A Parametric Contextual Online Learning Theory of Brokerage
François Bachoc, Tommaso Cesari, Roberto Colomboni
A Peer-review Look on Multi-modal Clustering: An Information Bottleneck Realization Method
Zhengzheng Lou, Hang Xue, Chaoyang Zhang et al.
A Physics-Augmented Deep Learning Framework for Classifying Single Molecule Force Spectroscopy Data
Cailong Hua, Sivaraman Rajaganapathy, Rebecca Slick et al.
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems
Manan Tayal, Aditya Singh, Shishir Nadubettu Yadukumar et al.
Approximate Differential Privacy of the $\ell_2$ Mechanism
Matthew Joseph, Alex Kulesza, Alexander Yu
Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees
Nate Veldt, Thomas Stanley, Benjamin Priest et al.
Approximately Correct Label Distribution Learning
Weiwei Li, Haitao Wu, Yunan Lu et al.
Approximating Latent Manifolds in Neural Networks via Vanishing Ideals
Nico Pelleriti, Max Zimmer, Elias Wirth et al.
Approximation to Smooth Functions by Low-Rank Swish Networks
Zimeng Li, Hongjun LI, Jingyuan Wang et al.
A-PSRO: A Unified Strategy Learning Method with Advantage Metric for Normal-form Games
Yudong Hu, Haoran Li, Congying Han et al.
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
Da Long, Zhitong Xu, Guang Yang et al.
Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
Thomas Fel, Ekdeep Singh Lubana, Jacob Prince et al.
A Reasoning-Based Approach to Cryptic Crossword Clue Solving
Martin Andrews, Sam Witteveen
A Recipe for Causal Graph Regression: Confounding Effects Revisited
Yujia Yin, Tianyi Qu, Zihao Wang et al.
A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
Zachary Roch, George Atia, Yue Wang
A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents
Kaiwen Wang, Dawen Liang, Nathan Kallus et al.
Are High-Quality AI-Generated Images More Difficult for Models to Detect?
Yao Xiao, Binbin Yang, Weiyan Chen et al.
Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
Na Lee, Konstantinos Barmpas, Yannis Panagakis et al.
Are Large Language Models Ready for Multi-Turn Tabular Data Analysis?
Jinyang Li, Nan Huo, Yan Gao et al.
A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni, Josh Engels, Senthooran Rajamanoharan et al.
Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang et al.
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
MYUNG-SIK CHO, Jong Eui Park, Jeonghye Kim et al.
A Sample Efficient Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Xinshuai Dong et al.
A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
Swetha Ganesh, Washim Mondal, Vaneet Aggarwal
A Simple Model of Inference Scaling Laws
Noam Levi