ICML

2022–2026 LIVE

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Machine Learning

2026 · 6,341 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。

2026 · ICML
Expanding the AI Evaluation Toolbox with Statistical Models
Drew Keller, Kweku Kwegyir-Aggrey, Ryan Steed, Anita K Rao, Julia Sharp, A. Bergman
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expanding the Capabilities of Reinforcement Learning via Text Feedback
Yuda Song, Lili Chen, Fahim Tajwar, REMI MUNOS, Deepak Pathak, J. Bagnell, Aarti Singh, Andrea Zanette
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expanding the Chaos: Neural Operator for Stochastic (Partial) Differential Equations
Dai Shi, Lequan Lin, Andi Han, Luke Thompson, Jose Miguel Hernandez-Lobato, Zhiyong Wang, Junbin Gao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expectation Alignment of Language Models for Real-World User Expectations
Miaomiao Li, Yang Wang, Bin Liang, Shudong Liu, Zhiwei Zhang, Kam-Fai Wong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift
Jinzong Dong, Zhaohui Jiang, Bo Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling
Abhijeet Sinha, Sundari Elango, Dianbo Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expected Returns and Policy Inconsistency-Aware Offline Federated Deep Reinforcement Learning
Meng XU, Zhongying Chen, Weiwei Fu, Yan Li, Shuguang Wang, Jianping Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Experience Augmented Policy Optimization for LLM Reasoning
Jinda Lu, Kexin Huang, Junkang Wu, Shuo Yang, Jinghan Li, Chiyu Ma, Shaohang Wei, Xiang Wang, Guoyin Wang, Jingren Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Experience is the Best Teacher: Motivating Effective Exploration in Reinforcement Learning for LLMs
Wenjian Zhang, Kongcheng Zhang, Jiaxin Qi, Jianqiang Huang, Baisheng Lai
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Experience-Evolving Multi-Turn Tool-Use Agent with Hybrid Episodic–Procedural Memory
Sijia Li, Yuchen Huang, Zifan LIU, Zijian LI, Jingjing Fu, Lei Song, Jiang Bian, Jun Zhang, Rui Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expert-guided Clinical Text Augmentation via Query-Based Model Collaboration
Dongkyu Cho, Miao Zhang, Gregory Lyng, Rumi Chunara
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expert-level Leaf Cell Layout Generation via Preference-Optimized LLM
Yaohui Han, Rongliang Fu, Yanming Liu, Shuo Ren, Shuai Dong, Yunpeng Wang, Tinghuan Chen, Bei Yu, Tsung-Yi Ho
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ExpertWeaver: Unlocking the Inherent MoE in Dense LLMs with GLU Activation Patterns
Ziyu Zhao, Tong Zhu, Xin Yu, Zhi Zhang, Tiantian Fan, Jinluan Yang, Kun Kuang, Zhongyu Wei, Fei Wu, Yu Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Explainable Federated Learning via Global–Local Attribution Alignment
Dawood Wasif, Terrence Moore, Chang-Tien Lu, Jin-Hee Cho
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Explainable Forensics of Manipulated Segments in Untrimmed Long Videos
Yue Feng, Jingjing Li, Qijia Lu, Wei Ji, Jingrou Zhang, Fei Shen, Xiao Li, Yizhen Jia, Qiang Chen, Limin Wang, Wentong Li, Jie Qin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Explaining Concept Shift with Interpretable Feature Attribution
Ruiqi Lyu, Alistair Turcan, Bryan Wilder
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Explaining Data Mixing Scaling Laws
rui dai, SHURAN ZHENG
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Explanations are a Means to an End: Decision Theoretic Explanation Evaluation
Ziyang Guo, Berk Ustun, Jessica Hullman
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Explicit representation of germline and non-germline residues improves antibody language modeling
Jeonghyeon Kim, Nathaniel Blalock, Ameya Kulkarni, Kensuke Nakamura, Philip Romero
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Explicitly Modeling Censoring Produces Superior Survival Predictors
Shi-ang Qi, Yakun Yu, Russell Greiner
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploiting weight-space symmetries for approximating curvature
Artem Artemev, Rui Xia, Benjamin M. Boyd, Youjing Yu, Felix Dangel, Guillaume Hennequin, Alberto Bernacchia
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploration Hacking: Can LLMs Learn to Resist RL Training?
Yeonwoo Jang, Damon Falck, Joschka Cedric Braun, Nathalie Kirch, Achyutha Menon, Perusha Moodley, Scott Emmons, Roland S. Zimmermann, David Lindner
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploration-free Algorithms for Multi-group Mean Estimation
Ziyi Wei, Huaiyang Zhong, Xiaocheng Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploring 3D Dataset Pruning
Xiaohan Zhao, Xinyi Shang, Jiacheng Liu, Zhiqiang Shen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference
Pengfei Hu, Chang Lu, Feifan Liu, Yue Ning
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploring Data-Free LoRA Transferability for Video Diffusion Models
Yuchen Wang, Wenliang Zhong, Lichen Bai, zikai ZHOU, Shitong Shao, Bojun Cheng, Shuo Chen, Shuo Yang, Zeke Xie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploring More to Solve More: Boosting Diversity in Text Diffusion Models via Entropy-Based Guidance
Jingwei Zhang, Haoyu LEI, Zijin Feng, Jiacheng Sun, Farzan Farnia
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploring Motif-based Heterogeneous Graph Learning for ReDoS Detection
Hong Huang, Chengyu Yao, Rongchen Li, Weihao Su, Chengyao Peng, Haiming Chen, Guiyi He
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploring Nonlinear Pathway in Parameter Space for Machine Unlearning
Yingdan Shi, Ren Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exploring and Exploiting Stability in Latent Flow Matching
Rania Briq, Michael Kamp, Ohad Fried, Sarel Cohen, Stefan Kesselheim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expo-GS: Exposure-Aware Signed Distance Function in Gaussian Splatting for High Dynamic Range
Chaoda Song, Yiren Lu, Xinpeng Li, Yunlai Zhou, Yanyan Zhang, Yu Yin, Vipin Chaudhary
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exposing Hidden Biases in Text-to-Image Models via Automated Prompt Search
Manos Plitsis, Giorgos Bouritsas, Vassilis Katsouros, Yannis Panagakis
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks
Bohan Wang, Zewen Liu, Lu Lin, Hui Liu, Li Xiong, Ming Jin, Wei Jin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expressive Graph Neural Networks via Equivariant Use of Noise
Xiyuan Wang, Muhan Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models
John Cooper, Ilias Diakonikolas, Mingchen Ma, Frederic Sala
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods
Felix Störck, Fabian Hinder, CITEC Barbara Hammer
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Extending Prediction-Powered Inference through Conformal Prediction
Daniel Csillag, Pedro Dall’Antonia, Claudio Struchiner, Guilherme Tegoni Goedert
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Extra-Merge: Tracing the Rank-1 Subspace of Model Merging in Language Model Pre-Training
WenJie Zhou, Bohan Wang, Hongtao Zhang, Chenxi Jia, Wei Chen, Xueqi Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Extracting alignment data in open models
Federico Barbero, Xiangming Gu, Christopher A. Choquette Choo, Chawin Sitawarin, Matthew Jagielski, Itay Yona, Petar Veličković, Ilia Shumailov, Jamie Hayes
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Eyes-on-Me: Scalable RAG Poisoning through Transferable Attention-Steering Attractors
Yen-Shan Chen, Sian-Yao Huang, Cheng-Lin Yang, Yun-Nung Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
E²I-VRWKV: Explicit EPI-Representation and Interaction-Aware Vision-RWKV for Light Field Semantic Segmentation
Wei Zhang, Chen Jia, Xu Cheng, Fan Shi, Hui Liu, Shengyong Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FAB: A First-Order AB-based Gradient Algorithm for Distributed Bilevel Optimization over Time-Varying Directed Graphs
Yaoshuai Ma, Xiao Wang, Wei Yao, Jin Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FACT: Fuzzy Alignment with Comorbidity Topology for Reliable Multi-Label Medical Image Diagnosis
Yingyu Chen, Yongqiang Huang, Yang Qin, Ziyuan Yang, Lang Yuan, Maosong Ran, Yi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FAFO: Lossy KV Cache Compression for Lossless Inference Acceleration via Draftless Fumble Decoding
Hoang Anh Duy Le, Shaochen (Henry) Zhong, Yifan Lu, Yingtong Dou, Jiayi Yuan, Yu-Neng Chuang, Xiran Fan, Guanchu Wang, Yuzhong Chen, Xia Hu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FAIL: Flow Matching Adversarial Imitation Learning for Image Generation
Yeyao Ma, Chen Li, Xiaosong Zhang, Han Hu, Weidi Xie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models
Haoyu Huang, Linlin Yang, Sheng Xu, Boyu Liu, Guodong Guo, Zhongqian Fu, Hang Zhou, Baochang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FAST-AR: Fast Autoregressive Video Diffusion and World Models with Temporal Cache Compression and Sparse Attention
Dvir Samuel, Issar Tzachor, Matan Levy, Michael Green, Gal Chechik, Rami Ben-Ari
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FG-CLIP 2: A Bilingual Fine-grained Vision-Language Alignment Model
Chunyu Xie, Bin Wang, Fanjing Kong, Jincheng Li, Dawei Liang, Ji Ao, Dawei Leng, Yuhui Yin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FIBER: A Differentially Private Optimizer with Filter-Aware Innovation Bias Correction
MINH DUC DO, Thao Do, Minh Hoang, Anh Le Duc Tran, Daeyoung Kim, Huy L Nguyen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FIDIA: Function-Informed Sequence Design via Inference-Aligned Policy Optimization
Minghan Li, fengji Li, Yilin Tao, Yue Deng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FIPN: Forward Self-Organizing Interpretable Polynomial Networks for Time Series Forecasting
YiZhen Wang, Zheng Wang, EUN-HU KIM, Zunwei Fu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FIRE-Bench: Evaluating AI Agents on the Rediscovery of Scientific Insights
Zhen Wang, Fan Bai, Zhongyan Luo, Jinyan Su, Kaiser Sun, Xinle Yu, Jieyuan Liu, Kun Zhou, Claire Cardie, Mark Dredze, Zhiting Hu, Eric Xing
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FIRE: Learning to Navigate and Act on Real-World Files via Stateful Reinforcement Learning
Jingyuan Ma, Zheng Li, Rui Li, Siyao Song, Ying Zeng, MINGHAO LI, Zhifang Sui
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FIRE: Multi-fidelity Regression with Distribution-conditioned In-context Learning using Tabular Foundation Models
Rosen Yu, Nicholas Sung, Faez Ahmed
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FLAC: Maximum Entropy RL via Kinetic Energy Regularized Bridge Matching
Lei Lyu, Yunfei Li, Yu Luo, Fuchun Sun, Xiao Ma
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
Qi Si, Penglei Wang, Yushuai Wu, Yifeng Jiao, Xuyang Liu, Xin Guo, Yuan Qi, Yuan Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FLARE-AI: Flaw Reporting for AI
Shayne Longpre, Elaine Zhu, Carson Ezell, Avijit Ghosh, Sean McGregor, Kevin Paeth, Kevin Klyman, Sayash Kapoor, Rishi Bommasani, Ruth Elisabeth Appel, Gregory Strom, Lauren McIlvenny, Mark Jaycox, Peter Slattery, Nathan Butters, Arvind Narayanan, Percy Liang, Alex Pentland
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FLIP2: Expanding Protein Fitness Landscape Benchmarks for Real-World Machine Learning Applications
Kieran Didi, Sarah Alamdari, Alex Lu, Bruce Wittmann, Kadina Johnston, Ava Amini, Ali Madani, Maya Czeneszew, Christian Dallago, Kevin Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences
Richardeau Gurvan, Gohar Dashyan, Erwan Le Merrer, Gilles Tredan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FOAM: Blocked State Folding for Memory-Efficient LLM Training
Ziqing Wen, Jiahuan Wang, ping luo, Dongsheng Li, Tao Sun
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FOAM: Frequency and Operator-Error Based Adaptive Damping Method for Reducing Staleness-Oriented Error for Shampoo
Kyunghun Nam, Sumyeong Ahn
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
Duc Nguyen, Nghiem Diep, Binh Nguyen Gia, Trong-Bao Ho, Doanh Le Thien, Quang Nguyen, Thien-Loc Ha, Tran Van Nhiem, Bao Thach, Tran Nhat, Tuan Tran, Artur Habuda, Philip Lund Møller, Tran Nguyen Le, Daniel Sonntag, Mathias Niepert, Khoa Doan, Vu Duong, Hung Ngo, Minh VU, Duy Nguyen, An Thai Le, Vien Ngo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance For Pruned Large Language Models
Junyoung Lee, Sehyeon Park, Shinhyoung Jang, Seonha Ryu, Hojeong Kim, Hyunsei Lee, Il Suh, Yeseong Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FOCUS: DLLMs Know How to Tame Their Compute Bound
Kaihua Liang, Xin Tan, An Zhong, Hong Xu, Marco Canini
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FOCUS: Forcing In-Context Object Localization through Visual Support Constraints and Policy Optimization
Mohammed Asad Karim, Vinay Kumar Verma
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FOVI: A biologically-inspired foveated interface for deep vision models
Nicholas Blauch, George Alvarez, Talia Konkle
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FPTQuant: Function-Preserving Transforms for LLM Quantization
Boris van Breugel, Yelysei Bondarenko, Paul Whatmough, Markus Nagel
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FRACTAL: State Space Model with Fractional Recurrent Architecture for Computational Temporal Analysis of Long Sequences
Mengqi Li, Wensheng Lin, Jinshuai Yang, Lixin Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FRIGID: Scaling Diffusion-Based Molecular Generation from Mass Spectra at Training and Inference Time
Montgomery Bohde, Hongxuan Liu, Mrunali Manjrekar, Magdalena Lederbauer, Shuiwang Ji, Runzhong Wang, Connor Coley
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FRISM: Fine-Grained Reasoning Injection via Subspace-Level Model Merging for Vision–Language Models
Chenyu Huang, Peng Ye, Xudong Tan, Jinhan Mu, Shenghe Zheng, Li Shen, Tao Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FS-I2P: A Hierarchical Focus–Sweep Registration Network with Dynamically Allocated Depth
Zhixin Cheng, Yujia Chen, Xujing Tao, Bohao Liao, Xiaotian Yin, Baoqun Yin, Tianzhu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
Qizheng Li, Yifei Zhang, Xiao Yang, Xu Yang, Zhuo Wang, Bowen Xian, Weiqing Liu, Jiang Bian
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FUSE: Ensembling Verifiers with Zero Labeled Data
Joonhyuk Lee, Virginia L., Sarah Zhao, Yash Nair, Asher Spector, Regev Cohen, Emmanuel J Candes
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FUSE: FK-Steered Multi-Modal Flow Matching for Efficient Simulation-Based Posterior Estimation
Weichen Qin, Yufan Xie, Peihao Wang, Chia-Jui Chou, Minghui Du, Peng Xu, Ziren Luo, Yi Yang, Jingyi Yu, Bo Liang, Jiakai Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FUSE: Frequency-domain Unification and Spectral Energy Alignment for Multi-modal Object Re-Identification
Xuanhao Qi, Tom Luan, Yukang Zhang, Jinkai Zheng, su zhou, Shuwei Li, Lei Tan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FUSE: Full‑spectrum Unlearnable Examples via Spectral Equalization
Jiale Cai, Gezheng Xu, Zhihao Li, Ruiyi Fang, Ruizhi Pu, di wu, Qicheng Lao, Charles X. Ling, Boyu Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FUSE: Quantifying Uncertainty in Vision-Language Models by Bayesian Fusing Epistemic and Aleatoric Uncertainty
Harry Zhang, Luca Carlone
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FaPS: A General and Fast Training Method for Diffusion Models
Xianglu Wang, Bangxian Han, Hu Ding
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FactGuard: Agentic Video Misinformation Detection via Reinforcement Learning
Zehao Li, Hongwei Yu, Hao Jiang, Qiang Sheng, Yilong Xu, Baolong Bi, Yang Li, Zhenlong Yuan, Yujun Cai, Zhaoqi Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Factor-Wise Homogeneity of Slot-Attention for Continual Object-Centric Learning
Ilmin Kang, Hoyong Kim, Seungju Bang, Minwoo Kang, Kangil Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Factored Causal Representation Learning for Robust Reward Modeling in RLHF
Yupei Yang, Lin Yang, Wanxi Deng, Lin Qu, Fan Feng, Biwei Huang, Shikui Tu, Lei Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Factored Classifier-Free Guidance
Tian Xia, Fabio De Sousa Ribeiro, Rajat Rasal, Avinash Kori, Raghav Mehta, Ben Glocker
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Factored Gossip DiLoCo: Reducing Blocking Communication within DiLoCo
Chamin Hewa Koneputugodage, Thalaiyasingam Ajanthan, Sameera Ramasinghe, Hadi Mohaghegh Dolatabadi, Shamane Siriwardhana, Gil Avraham, Violetta Shevchenko, Karol Pajak, James Snewin, Alexander Long
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Factored Latent Action World Models
Zizhao Wang, Chang Shi, Jiaheng Hu, Kevin Rohling, Roberto Martín-Martín, Amy Zhang, Peter Stone
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Factored Value Functions for Graph-Based Multi-Agent Reinforcement Learning
Ahmed Rashwan, Keith Briggs, Chris Budd, Lisa Kreusser
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions
Hong Je-Gal, Hyun-Suk Lee
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization
Tina Behnia, Puneesh Deora, Christos Thrampoulidis
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Failure is Feedback: History-Aware Backtracking for Agentic Traversal in Multimodal Graphs
Joohyung Yun, Doyup Lee, Wook-Shin Han
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Failure-Driven Workflow Refinement
Jusheng Zhang, Jing Yang, Kaitong Cai, Ziliang Chen, Yongsen Zheng, Kwok Yan Lam, Liang Lin, Keze Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off
Maaya Sakata, Kazuto Fukuchi
Machine Learning
日本大学: 筑波大学
2026 · ICML
Fair Dataset Distillation via Cross-Group Barycenter Alignment
Mohammad Hossein Moslemi, Nima Hosseini Dashtbayaz, Zhimin Mei, Bissan Ghaddar, Boyu Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Fair Decisions from Calibrated Scores: Achieving Optimal Classification While Satisfying Sufficiency
Etam Benger, Katrina Ligett
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Fair Transit Stop Placement: A Clustering Perspective and Beyond
Haris Aziz, Ling Gai, Yuhang Guo, Jeremy Vollen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Fair-FedMOE: Group-Fair One-Shot Federated Learning via Prototype-Guided Experts for Medical Imaging Analysis
Lingzhao Meng, Shuai Guo, Weishan Zhang, Zengxiang Li, Han Yu, Nan Liu, Daniel Ting, Yuru Liu, Shudong Wang, Tao Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FairGB: A Fair Granular-Ball Generation Method for Data Classification
Qifen Yang, Yuhui Deng, Jiande Huang, Peng Zhou, Xiwen Lu, Lin Cui
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FairJudge : An Adaptive, Debiased, and Consistent LLM-as-a-Judge
Bo Yang, Lanfei Feng, Yunkui Chen, Xiao Xu, Yu Zhang, Shijian Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FairMerging: Rethinking Model Merging through the Lens of Fairness
Bing Liu, Xinrui Shan, Boyu Zhang, Qiankun Zhang, Bin Yuan, Wang, Xianjun Deng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FairRARI: A Plug and Play Framework for Fairness-Aware PageRank
Emmanouil Kariotakis, Aritra Konar
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
FairSSL: Fair Multimodal Self-Supervised Learning
Jiaee Cheong, Abtin Mogharabin, Paul Pu Liang, Hatice Gunes, Sinan Kalkan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking
Diptarka Chakraborty, Arya Mazumdar, Barna Saha, Alvin H Yan
Machine Learning
日本大学: 関与なし（対象大学）