ICML

2021–2025 確定版

著者一覧 · 国際会議 · 大学ランキング

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Machine Learning

2025 · 3,330 papers

このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。

2025 · ICML
Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks
Thomas Massena, Léo Andéol, Thibaut Boissin, Franck Mamalet, Corentin Friedrich, Mathieu Serrurier, Sébastien Gerchinovitz
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficient Skill Discovery via Regret-Aware Optimization
He Zhang, Ming Zhou, Shaopeng Zhai, Ying Sun, Hui Xiong
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization
Xiuyuan Wang, Chaochao Chen, Weiming Liu, Xinting Liao, Fan Wang, Xiaolin Zheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficient Time Series Processing for Transformers and State-Space Models through Token Merging
Leon Götz, Marcel Kollovieh, Stephan Günnemann, Leo Schwinn
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs
Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Christopher A. Choquette-Choo, Adam Dziedzic
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity
Erpai Luo, Xinran Wei, Lin Huang, Yunyang Li, Han Yang, Zaishuo Xia, Zun Wang, Chang Liu, Bin Shao, Jia Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficient and Separate Authentication Image Steganography Network
Junchao Zhou, Yao Lu, Jie Wen, Guangming Lu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficiently Access Diffusion Fisher: Within the Outer Product Span Space
Fangyikang Wang, Hubery Yin, Shaobin Zhuang, Huminhao Zhu, Yinan Li, Lei Qian, Chao Zhang, Hanbin Zhao, Hui Qian, Chen Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficiently Serving Large Multimodal Models Using EPD Disaggregation
Gursimran Singh, Xinglu Wang, Yifan Hu, Timothy Tin Long Yu, Linzi Xing, Wei Jiang, Zhefeng Wang, Bai Xiaolong, Yi Li, Ying Xiong, Yong Zhang, Zhenan Fan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Efficiently Vectorized MCMC on Modern Accelerators
Hugh Dance, Pierre Glaser, Peter Orbanz, Ryan P Adams
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EgoPrivacy: What Your First-Person Camera Says About You?
Yijiang Li, Genpei Zhang, Jiacheng Cheng, Yi Li, Xiaojun Shan, Dashan Gao, Jiancheng Lyu, Yuan Li, Ning Bi, Nuno Vasconcelos
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ehrenfeucht-Haussler Rank and Chain of Thought
Pablo Barcelo, Alexander Kozachinskiy, Tomasz Steifer
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Eigen Analysis of Conjugate Kernel and Neural Tangent Kernel
Xiangchao Li, Xiao Han, Qing Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
Yuanzhe Hu, Kinshuk Goel, Vlad Killiakov, Yaoqing Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Eliciting Language Model Behaviors with Investigator Agents
Xiang Lisa Li, Neil Chowdhury, Daniel D. Johnson, Tatsunori Hashimoto, Percy Liang, Sarah Schwettmann, Jacob Steinhardt
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Elucidating Flow Matching ODE Dynamics via Data Geometry and Denoisers
Zhengchao Wan, Qingsong Wang, Gal Mishne, Yusu Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Elucidating the Design Space of Multimodal Protein Language Models
Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang, Dongyu Xue, Fei Ye, Shujian Huang, Zaixiang Zheng, Quanquan Gu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Elucidating the design space of language models for image generation
Xuantong Liu, Shaozhe Hao, Xianbiao Qi, Tianyang Hu, Jun Wang, Rong Xiao, Yuan Yao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Embedding Safety into RL: A New Take on Trust Region Methods
Nikola Milosevic, Johannes Müller, Nico Scherf
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents
Rui Yang, Hanyang Chen, Junyu Zhang, Mark Zhao, Cheng Qian, Kangrui Wang, Qineng Wang, Teja Venkat Koripella, Marziyeh Movahedi, Manling Li, Heng Ji, Huan Zhang, Tong Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Emergence and Effectiveness of Task Vectors in In-Context Learning: An Encoder Decoder Perspective
Seungwook Han, Jinyeop Song, Jeff Gore, Pulkit Agrawal
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Emergence in non-neural models: grokking modular arithmetic via average gradient outer product
Neil Rohit Mallinar, Daniel Beaglehole, Libin Zhu, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs
Jan Betley, Daniel Chee Hian Tan, Niels Warncke, Anna Sztyber-Betley, Xuchan Bao, Martı́n Soto, Nathan Labenz, Owain Evans
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Emergent Response Planning in LLMs
Zhichen Dong, Zhanhui Zhou, Zhixuan Liu, Chao Yang, Chaochao Lu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models
Yukang Yang, Declan Iain Campbell, Kaixuan Huang, Mengdi Wang, Jonathan D. Cohen, Taylor Whittington Webb
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EmoGrowth: Incremental Multi-label Emotion Decoding with Augmented Emotional Relation Graph
Kaicheng Fu, Changde Du, Jie Peng, Kunpeng Wang, Shuangchen Zhao, Xiaoyu Chen, Huiguang He
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Emoji Attack: Enhancing Jailbreak Attacks Against Judge LLM Detection
Zhipeng Wei, Yuqi Liu, N. Benjamin Erichson
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Emotional Face-to-Speech
Jiaxin Ye, Boyuan Cao, Hongming Shan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Empirical Privacy Variance
Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David Forsyth
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networks
Keyue Qiu, Yuxuan Song, Jie Yu, Hongbo Ma, Ziyao Cao, Zhilong Zhang, Yushuai Wu, Mingyue Zheng, Hao Zhou, Wei-Ying Ma
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Empowering World Models with Reflection for Embodied Video Prediction
Xiaowei Chi, Chun-Kai Fan, Hengyuan Zhang, Xingqun Qi, Rongyu Zhang, Anthony Chen, Chi-Min Chan, Wei Xue, Qifeng Liu, Shanghang Zhang, Yike Guo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EnIGMA: Interactive Tools Substantially Assist LM Agents in Finding Security Vulnerabilities
Talor Abramovich, Meet Udeshi, Minghao Shao, Kilian Lieret, Haoran Xi, Kimberly Milner, Sofija Jancheska, John Yang, Carlos E Jimenez, Farshad Khorrami, Prashanth Krishnamurthy, Brendan Dolan-Gavitt, Muhammad Shafique, Karthik R Narasimhan, Ramesh Karri, Ofir Press
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enabling Optimal Decisions in Rehearsal Learning under CARE Condition
Wen-Bo Du, Hao-Yi Lei, Lue Tao, Tian-Zuo Wang, Zhi-Hua Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption
Leo De Castro, Daniel Escudero, Adya Agrawal, Antigoni Polychroniadou, Manuela Veloso
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
End-to-End Learning Framework for Solving Non-Markovian Optimal Control
Xiaole Zhang, Peiyu Zhang, Xiongye Xiao, Shixuan Li, Vasileios Tzoumas, Vijay Gupta, Paul Bogdan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Energy-Based Flow Matching for Generating 3D Molecular Structure
Wenyin Zhou, Christopher Iliffe Sprague, Vsevolod Viliuga, Matteo Tadiello, Arne Elofsson, Hossein Azizpour
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model
Yuzhong Hong, Hanshan Zhang, Junwei Bao, Hongfei Jiang, Yang Song
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enforcing Idempotency in Neural Networks
Nikolaj Banke Jensen, Jamie Vicary
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation
Alessandro Palma, Sergei Rybakov, Leon Hetzel, Stephan Günnemann, Fabian J Theis
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability
Jie Bao, Chuangyin Dang, Rui Luo, Hanwei Zhang, Zhixin Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss
Bo-Han Lai, Pin-Han Huang, Bo-Han Kung, Shang-Tse Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration
Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen, Giorgos Stamou, Michael M. Zavlanos, George Vouros
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Decision-Making of Large Language Models via Actor-Critic
Heng Dong, Kefei Duan, Chongjie Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Diversity In Parallel Agents: A Maximum State Entropy Exploration Story
Vincenzo De Paola, Riccardo Zamboni, Mirco Mutti, Marcello Restelli
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization
Luca Masserano, Abdul Fatir Ansari, Boran Han, Xiyuan Zhang, Christos Faloutsos, Michael W. Mahoney, Andrew Gordon Wilson, Youngsuk Park, Syama Sundar Rangapuram, Danielle C. Maddix, Bernie Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Foundation Models with Federated Domain Knowledge Infusion
Jiaqi Wang, Jingtao Li, Weiming Zhuang, Chen Chen, Lingjuan Lyu, Fenglong Ma
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of Invariance
Yusong Wang, Shiyin Tan, Jialun Shen, Yicheng Xu, Haobo Song, Qi Xu, Prayag Tiwari, Mingkun Xu
Machine Learning
日本大学: 東京科学大学 / 東京大学
2025 · ICML
Enhancing Graph Invariant Learning from a Negative Inference Perspective
Kuo Yang, Zhengyang Zhou, Qihe Huang, Wenjie Du, Limin Li, Wu Jiang, Yang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward Optimization
Seungbeom Lee, Munsun Jo, Jungseul Ok, Dongwoo Kim
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Logits Distillation with Plug&Play Kendall’s $τ$ Ranking Loss
Yuchen Guan, Runxi Cheng, Kang Liu, Chun Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Parallelism in Decentralized Stochastic Convex Optimization
Ofri Eisen, Ron Dorfman, Kfir Yehuda Levy
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Performance of Explainable AI Models with Constrained Concept Refinement
Geyu Liang, Senne Michielssen, Salar Fattahi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models
Tung Minh Luu, Younghwan Lee, Donghoon Lee, Sunho Kim, Min Jun Kim, Chang D. Yoo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Spectral GNNs: From Topology and Perturbation Perspectives
Taoyang Qin, Ke-Jia Chen, Zheng Liu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Statistical Validity and Power in Hybrid Controlled Trials: A Randomization Inference Approach with Conformal Selective Borrowing
Ke Zhu, Shu Yang, Xiaofei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Target-unspecific Tasks through a Features Matrix
Fangming Cui, Yonggang Zhang, Xuan Wang, Xinmei Tian, Jun Yu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong, Li Kheng Chai, Shazia Sadiq, Hongzhi Yin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing Visual Localization with Cross-Domain Image Generation
Yuanze Wang, Yichao Yan, Shiming Song, Songchang Jin, Yilan Huang, Xingdong Sheng, Dianxi Shi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks
Jincheng Huang, Yujie Mo, Xiaoshuang Shi, Lei Feng, Xiaofeng Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification
Ben Dai
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ensemble Distribution Distillation via Flow Matching
Jonggeon Park, Giung Nam, Hyunsu Kim, Jongmin Yoon, Juho Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ensemble Learned Bloom Filters: Two Oracles are Better than One
Ming Lin, Lin Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EpiCoder: Encompassing Diversity and Complexity in Code Generation
Yaoxiang Wang, Haoling Li, Xin Zhang, Jie Wu, Xiao Liu, Wenxiang Hu, Zhongxin Guo, Yangyu Huang, Ying Xin, Yujiu Yang, Jinsong Su, Qi Chen, Scarlett Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Epsilon-VAE: Denoising as Visual Decoding
Long Zhao, Sanghyun Woo, Ziyu Wan, Yandong Li, Han Zhang, Boqing Gong, Hartwig Adam, Xuhui Jia, Ting Liu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations
Haotian Zhai, Connor Lawless, Ellen Vitercik, Liu Leqi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Equivalence is All: A Unified View for Self-supervised Graph Learning
Yejiang Wang, Yuhai Zhao, Zhengkui Wang, Ling Li, Jiapu Wang, Fangting Li, Miaomiao Huang, Shirui Pan, Xingwei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Equivariant Neural Tangent Kernels
Philipp Misof, Pan Kessel, Jan E Gerken
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Equivariant Polynomial Functional Networks
Thieu Vo, Hoang V. Tran, Tho Tran Huu, An Nguyen The, Thanh Tran, Minh-Khoi Nguyen-Nhat, Duy-Tung Pham, Tan Minh Nguyen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers
Daiheng Gao, Shilin Lu, Wenbo Zhou, Jiaming Chu, Jie Zhang, Mengxi Jia, Bang Zhang, Zhaoxin Fan, Weiming Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ergodic Generative Flows
Leo Maxime Brunswic, Mateo Clémente, Rui Heng Yang, Adam Sigal, Amir Rasouli, Yinchuan Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems
Maksim Zhdanov, Max Welling, Jan-Willem Van De Meent
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EvFocus: Learning to Reconstruct Sharp Images from Out-of-Focus Event Streams
Lin Zhu, Xiantao Ma, Xiao Wang, Lizhi Wang, Hua Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling Evaluators
Yilun Zhou, Austin Xu, Peifeng Wang, Caiming Xiong, Shafiq Joty
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving
Yuxuan Zhou, Xien Liu, Chenwei Yan, Chen Ning, Xiao Zhang, Boxun Li, Xiangling Fu, Shijin Wang, Guoping Hu, Yu Wang, Ji Wu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Evaluating Neuron Explanations: A Unified Framework with Sanity Checks
Tuomas Oikarinen, Ge Yan, Tsui-Wei Weng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Event-Customized Image Generation
Zhen Wang, Yilei Jiang, Dong Zheng, Jun Xiao, Long Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition
Zheyang Xiong, Ziyang Cai, John Cooper, Albert Ge, Vasilis Papageorgiou, Zack Sifakis, Angeliki Giannou, Ziqian Lin, Liu Yang, Saurabh Agarwal, Grigorios Chrysos, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EvoControl: Multi-Frequency Bi-Level Control for High-Frequency Continuous Control
Samuel Holt, Todor Davchev, Dhruva Tirumala, Ben Moran, Atil Iscen, Antoine Laurens, Yixin Lin, Erik Frey, Markus Wulfmeier, Francesco Romano, Nicolas Heess
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EvoMesh: Adaptive Physical Simulation with Hierarchical Graph Evolutions
Huayu Deng, Xiangming Zhu, Yunbo Wang, Xiaokang Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
EvoPress: Accurate Dynamic Model Compression via Evolutionary Search
Oliver Sieberling, Denis Kuznedelev, Eldar Kurtic, Dan Alistarh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Evolving Minds: Logic-Informed Inference from Temporal Action Patterns
Chao Yang, Shuting Cui, Yang Yang, Shuang Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective
Jianyu Wang, Zhiqiang Hu, Lidong Bing
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ex-VAD: Explainable Fine-grained Video Anomaly Detection Based on Visual-Language Models
Chao Huang, Yushu Shi, Jie Wen, Wei Wang, Yong Xu, Xiaochun Cao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ExLM: Rethinking the Impact of $\texttt[MASK]$ Tokens in Masked Language Models
Kangjie Zheng, Junwei Yang, Siyue Liang, Bin Feng, Zequn Liu, Wei Ju, Zhiping Xiao, Ming Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts
Samar Khanna, Medhanie Irgau, David B. Lobell, Stefano Ermon
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements
Arya Mazumdar, Neha Sangwan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Exact Upper and Lower Bounds for the Output Distribution of Neural Networks with Random Inputs
Andrey Kofnov, Daniel Kapla, Ezio Bartocci, Efstathia Bura
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Exact risk curves of signSGD in High-Dimensions: quantifying preconditioning and noise-compression effects
Ke Liang Xiao, Noah Marshall, Atish Agarwala, Elliot Paquette
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Exactly Tight Information-theoretic Generalization Bounds via Binary Jensen-Shannon Divergence
Yuxin Dong, Haoran Guo, Tieliang Gong, Wen Wen, Chen Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Exogenous Isomorphism for Counterfactual Identifiability
Yikang Chen, Dehui Du
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ExpProof : Operationalizing Explanations for Confidential Models with ZKPs
Chhavi Yadav, Evan Laufer, Dan Boneh, Kamalika Chaudhuri
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Expected Variational Inequalities
Brian Hu Zhang, Ioannis Anagnostides, Emanuel Tewolde, Ratip Emin Berker, Gabriele Farina, Vincent Conitzer, Tuomas Sandholm
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts
Yike Yuan, Ziyu Wang, Zihao Huang, Defa Zhu, Xun Zhou, Jingyi Yu, Qiyang Min
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks’ Internal Representations
Aditya Taparia, Som Sagar, Ransalu Senanayake
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Explaining the role of Intrinsic Dimensionality in Adversarial Training
Enes Altinisik, Safa Messaoud, Husrev Taha Sencar, Hassan Sajjad, Sanjay Chawla
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations
Shahaf Bassan, Yizhak Yisrael Elboher, Tobias Ladner, Matthias Althoff, Guy Katz
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Explanatory Instructions: Towards Unified Vision Tasks Understanding and Zero-shot Generalization
Yang Shen, Xiu-Shen Wei, Yifan Sun, Yuxin Song, Tao Yuan, Jian Jin, He-Yang Xu, Yazhou Yao, Errui Ding
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Explicit Discovery of Nonlinear Symmetries from Dynamic Data
Lexiang Hu, Yikang Li, Zhouchen Lin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Explicit Exploration for High-Welfare Equilibria in Game-Theoretic Multiagent Reinforcement Learning
Austin A. Nguyen, Anri Gu, Michael P. Wellman
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Explicit Preference Optimization: No Need for an Implicit Reward Model
Xiangkun Hu, Lemin Kong, Tong He, David Wipf
Machine Learning
日本大学: 関与なし（対象大学）