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
Delay-DSGN: A Dynamic Spiking Graph Neural Network with Delay Mechanisms for Evolving Graph
Zhiqiang Wang, Jianghao Wen, Jianqing Liang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Deliberation in Latent Space via Differentiable Cache Augmentation
Luyang Liu, Jonas Pfeiffer, Jiaxing Wu, Jun Xie, Arthur Szlam
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Delta Decompression for MoE-based LLMs Compression
Hao Gu, Wei Li, Lujun Li, Zhu Qiyuan, Mark G. Lee, Shengjie Sun, Wei Xue, Yike Guo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Demeaned Sparse: Efficient Anomaly Detection by Residual Estimate
Yifan Fang, Yifei Fang, Ruizhe Chen, Haote Xu, Xinghao Ding, Yue Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Demonstration Selection for In-Context Learning via Reinforcement Learning
Xubin Wang, Jianfei Wu, Yuan Yichen, Deyu Cai, Mingzhe Li, Weijia Jia
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector
Qirui Wu, Shizhou Zhang, De Cheng, Yinghui Xing, Di Xu, Peng Wang, Yanning Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
Youhe Jiang, Fangcheng Fu, Xiaozhe Yao, Guoliang He, Xupeng Miao, Ana Klimovic, Bin Cui, Binhang Yuan, Eiko Yoneki
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Demystifying Long Chain-of-Thought Reasoning
Shiming Yang, Yuxuan Tong, Xinyao Niu, Graham Neubig, Xiang Yue
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Demystifying Singular Defects in Large Language Models
Haoqi Wang, Tong Zhang, Mathieu Salzmann
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
Hongyi Zhou, Josiah P. Hanna, Jin Zhu, Ying Yang, Chengchun Shi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Dendritic Localized Learning: Toward Biologically Plausible Algorithm
Changze Lv, Jingwen Xu, Yiyang Lu, Xiaohua Wang, Zhenghua Wang, Zhibo Xu, Di Yu, Xin Du, Xiaoqing Zheng, Xuanjing Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Density Ratio Estimation with Conditional Probability Paths
Hanlin Yu, Arto Klami, Aapo Hyvarinen, Anna Korba, Omar Chehab
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning
Jungtaek Kim
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li, Junmei Yang, John Paisley, Delu Zeng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Design Considerations in Offline Preference-based RL
Alekh Agarwal, Christoph Dann, Teodor Vanislavov Marinov
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Designing Cyclic Peptides via Harmonic SDE with Atom-Bond Modeling
Xiangxin Zhou, Mingyu Li, Yi Xiao, Jiahan Li, Dongyu Xue, Zaixiang Zheng, Jianzhu Ma, Quanquan Gu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Detecting Strategic Deception with Linear Probes
Nicholas Goldowsky-Dill, Bilal Chughtai, Stefan Heimersheim, Marius Hobbhahn
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Determinant Estimation under Memory Constraints and Neural Scaling Laws
Siavash Ameli, Chris Van Der Heide, Liam Hodgkinson, Fred Roosta, Michael W. Mahoney
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Determining Layer-wise Sparsity for Large Language Models Through a Theoretical Perspective
Weizhong Huang, Yuxin Zhang, Xiawu Zheng, Fei Chao, Rongrong Ji
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Deterministic Sparse Fourier Transform for Continuous Signals with Frequency Gap
Xiaoyu Li, Zhao Song, Shenghao Xie
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
Rafal Karczewski, Markus Heinonen, Vikas K Garg
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DexScale: Automating Data Scaling for Sim2Real Generalizable Robot Control
Guiliang Liu, Yueci Deng, Runyi Zhao, Huayi Zhou, Jian Chen, Jietao Chen, Ruiyan Xu, Yunxin Tai, Kui Jia
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation
Shuyuan Wang, Philip D Loewen, Michael Forbes, Bhushan Gopaluni, Wei Pan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DiMa: Understanding the Hardness of Online Matching Problems via Diffusion Models
Boyu Zhang, Aocheng Shen, Bing Liu, Qiankun Zhang, Bin Yuan, Jing Wang, Shenghao Liu, Xianjun Deng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
Dongya Jia, Zhuo Chen, Jiawei Chen, Chenpeng Du, Jian Wu, Jian Cong, Xiaobin Zhuang, Chumin Li, Zhen Wei, Yuping Wang, Yuxuan Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrödinger Equation
Kevin Han Huang, Ni Zhan, Elif Ertekin, Peter Orbanz, Ryan P Adams
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Dialogue Without Limits: Constant-Sized KV Caches for Extended Response in LLMs
Ravi Ghadia, Avinash Kumar, Gaurav Jain, Prashant J. Nair, Poulami Das
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diff-MoE: Diffusion Transformer with Time-Aware and Space-Adaptive Experts
Kun Cheng, Xiao He, Lei Yu, Zhijun Tu, Mingrui Zhu, Nannan Wang, Xinbo Gao, Jie Hu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DiffAdvMAP: Flexible Diffusion-Based Framework for Generating Natural Unrestricted Adversarial Examples
Zhengzhao Pan, Hua Chen, Xiaogang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra
Montgomery Bohde, Mrunali Manjrekar, Runzhong Wang, Shuiwang Ji, Connor W. Coley
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differentiable Quadratic Optimization For the Maximum Independent Set Problem
Ismail Alkhouri, Cedric Le Denmat, Yingjie Li, Cunxi Yu, Jia Liu, Rongrong Wang, Alvaro Velasquez
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differentiable Solver Search for Fast Diffusion Sampling
Shuai Wang, Zexian Li, Qipeng Zhang, Tianhui Song, Xubin Li, Tiezheng Ge, Bo Zheng, Limin Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differentiable Structure Learning with Ancestral Constraints
Taiyu Ban, Changxin Rong, Xiangyu Wang, Lyuzhou Chen, Xin Wang, Derui Lyu, Qinrui Zhu, Huanhuan Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu, Peng Xue, Zecheng Hao, Wenxuan Liu, Yuanhong Tang, Zhaofei Yu, Tiejun Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms
Andrea Bertazzi, Tim Johnston, Gareth O. Roberts, Alain Oliviero Durmus
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differential Privacy Under Class Imbalance: Methods and Empirical Insights
Lucas Rosenblatt, Yuliia Lut, Ethan Turok, Marco Avella Medina, Rachel Cummings
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
Ce Zhang, Yixin Han, Yafei Wang, Xiaodong Yan, Linglong Kong, Ting Li, Bei Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differentially Private Boxplots
Kelly Ramsay, Jairo Diaz-Rodriguez
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differentially Private Federated $k$-Means Clustering with Server-Side Data
Jonathan Scott, Christoph H. Lampert, David Saulpic
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
Rachel Cummings, Alessandro Epasto, Jieming Mao, Tamalika Mukherjee, Tingting Ou, Peilin Zhong
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
Kevin Rojas, Yuchen Zhu, Sichen Zhu, Felix X-F. Ye, Molei Tao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffusion Adversarial Post-Training for One-Step Video Generation
Shanchuan Lin, Xin Xia, Yuxi Ren, Ceyuan Yang, Xuefeng Xiao, Lu Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffusion Counterfactual Generation with Semantic Abduction
Rajat R Rasal, Avinash Kori, Fabio De Sousa Ribeiro, Tian Xia, Ben Glocker
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffusion Instruction Tuning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran, Tom Diethe, Philip Alexander Teare
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
Hengyuan Hu, Aniket Das, Dorsa Sadigh, Nima Anari
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffusion Sampling Correction via Approximately 10 Parameters
Guangyi Wang, Wei Peng, Lijiang Li, Wenyu Chen, Yuren Cai, Song-Zhi Su
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors
Emile Pierret, Bruno Galerne
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffusion on Language Model Encodings for Protein Sequence Generation
Viacheslav Meshchaninov, Pavel Strashnov, Andrey Shevtsov, Fedor Nikolaev, Nikita Ivanisenko, Olga Kardymon, Dmitry Vetrov
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Gaozheng Pei, Ke Ma, Yingfei Sun, Qianqian Xu, Qingming Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DiffusionVLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression
Junjie Wen, Yichen Zhu, Minjie Zhu, Zhibin Tang, Jinming Li, Zhongyi Zhou, Xiaoyu Liu, Chaomin Shen, Yaxin Peng, Feifei Feng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Dimension-Free Adaptive Subgradient Methods with Frequent Directions
Sifan Yang, Yuanyu Wan, Peijia Li, Yibo Wang, Xiao Zhang, Zhewei Wei, Lijun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Dimension-Independent Rates for Structured Neural Density Estimation
Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Dimensionality Reduction on Complex Vector Spaces for Euclidean Distance with Dynamic Weights
Simone Moretti, Paolo Pellizzoni, Francesco Silvestri
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DipLLM: Fine-Tuning LLM for Strategic Decision-making in Diplomacy
Kaixuan Xu, Jiajun Chai, Sicheng Li, Yuqian Fu, Yuanheng Zhu, Dongbin Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Direct Density Ratio Optimization: A Statistically Consistent Approach to Aligning Large Language Models
Rei Higuchi, Taiji Suzuki
Machine Learning
日本大学: 東京大学
2025 · ICML
Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator
Kaiwen Zheng, Yongxin Chen, Huayu Chen, Guande He, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Direct Motion Models for Assessing Generated Videos
Kelsey R Allen, Carl Doersch, Guangyao Zhou, Mohammed Suhail, Danny Driess, Ignacio Rocco, Yulia Rubanova, Thomas Kipf, Mehdi S. M. Sajjadi, Kevin Patrick Murphy, Joao Carreira, Sjoerd Van Steenkiste
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Direct Prediction Set Minimization via Bilevel Conformal Classifier Training
Yuanjie Shi, Hooman Shahrokhi, Xuesong Jia, Xiongzhi Chen, Jana Doppa, Yan Yan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Directed Graph Grammars for Sequence-based Learning
Michael Sun, Orion Foo, Gang Liu, Wojciech Matusik, Jie Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Directly Forecasting Belief for Reinforcement Learning with Delays
Qingyuan Wu, Yuhui Wang, Simon Sinong Zhan, Yixuan Wang, Chung-Wei Lin, Chen Lv, Qi Zhu, Jürgen Schmidhuber, Chao Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
Vicente Balmaseda, Bokun Wang, Ching-Long Lin, Tianbao Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discovering Latent Causal Graphs from Spatiotemporal Data
Kun Wang, Sumanth Varambally, Duncan Watson-Parris, Yian Ma, Rose Yu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discovering Physics Laws of Dynamical Systems via Invariant Function Learning
Shurui Gui, Xiner Li, Shuiwang Ji
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discovering Spoofing Attempts on Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discovering Symbolic Cognitive Models from Human and Animal Behavior
Pablo Samuel Castro, Nenad Tomasev, Ankit Anand, Navodita Sharma, Rishika Mohanta, Aparna Dev, Kuba Perlin, Siddhant Jain, Kyle Levin, Noemi Elteto, Will Dabney, Alexander Novikov, Glenn C Turner, Maria K Eckstein, Nathaniel D. Daw, Kevin J Miller, Kim Stachenfeld
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discovering a Zero (Zero-Vector Class of Machine Learning)
Harikrishna Metta, Venkatesh Babu Radhakrishnan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension
Yijun Dong, Yicheng Li, Yunai Li, Jason D. Lee, Qi Lei
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discrepancy Minimization in Input-Sparsity Time
Yichuan Deng, Xiaoyu Li, Zhao Song, Omri Weinstein
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
Le-Tuyet-Nhi Pham, Dario Shariatian, Antonio Ocello, Giovanni Conforti, Alain Oliviero Durmus
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discrete Neural Algorithmic Reasoning
Gleb Rodionov, Liudmila Prokhorenkova
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discrete and Continuous Difference of Submodular Minimization
George Orfanides, Tim Hoheisel, Marwa El Halabi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data
Siqi Guo, Ilgee Hong, Vicente Balmaseda, Changlong Yu, Liang Qiu, Xin Liu, Haoming Jiang, Tuo Zhao, Tianbao Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Discriminative Policy Optimization for Token-Level Reward Models
Hongzhan Chen, Tao Yang, Shiping Gao, Ruijun Chen, Xiaojun Quan, Hongtao Tian, Ting Yao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Disentangled Graph Spectral Domain Adaptation
Liang Yang, Xin Chen, Jiaming Zhuo, Di Jin, Chuan Wang, Xiaochun Cao, Zhen Wang, Yuanfang Guo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts
Haoyang Li, Xin Wang, Xueling Zhu, Weigao Wen, Wenwu Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Disentangling and Integrating Relational and Sensory Information in Transformer Architectures
Awni Altabaa, John Lafferty
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Disparate Conditional Prediction in Multiclass Classifiers
Sivan Sabato, Eran Treister, Elad Yom-Tov
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic Transforms
Julius von Rohrscheidt, Bastian Rieck
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies
Yuefan Cao, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Jiahao Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs
Jongwoo Ko, Tianyi Chen, Sungnyun Kim, Tianyu Ding, Luming Liang, Ilya Zharkov, Se-Young Yun
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distillation Scaling Laws
Dan Busbridge, Amitis Shidani, Floris Weers, Jason Ramapuram, Etai Littwin, Russell Webb
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distillation of Discrete Diffusion through Dimensional Correlations
Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi, Hiromi Wakaki, Yuki Mitsufuji
Machine Learning
日本大学: 東京大学
2025 · ICML
Distilling the Knowledge in Data Pruning
Emanuel Ben Baruch, Adam Botach, Igor Kviatkovsky, Manoj Aggarwal, Gerard Medioni
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distinguishing Cause from Effect with Causal Velocity Models
Johnny Xi, Hugh Dance, Peter Orbanz, Benjamin Bloem-Reddy
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributed Conformal Prediction via Message Passing
Haifeng Wen, Hong Xing, Osvaldo Simeone
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributed Differentially Private Data Analytics via Secure Sketching
Jakob Burkhardt, Hannah Keller, Claudio Orlandi, Chris Schwiegelshohn
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributed Event-Based Learning via ADMM
Guner Dilsad Er, Sebastian Trimpe, Michael Muehlebach
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributed Nonparametric Estimation: from Sparse to Dense Samples per Terminal
Deheng Yuan, Tao Guo, Zhongyi Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributed Parallel Gradient Stacking(DPGS): Solving Whole Slide Image Stacking Challenge in Multi-Instance Learning
Boyuan Wu, Zefeng Wang, Xianwei Lin, Jiachun Xu, Jikai Yu, Zhou Shicheng, Hongda Chen, Lianxin Hu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold
Yilong Song, Peijin Li, Bin Gao, Kun Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective
Yujin Oh, Pengfei Jin, Sangjoon Park, Sekeun Kim, Siyeop Yoon, Jin Sung Kim, Kyungsang Kim, Xiang Li, Quanzheng Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributional Diffusion Models with Scoring Rules
Valentin De Bortoli, Alexandre Galashov, J Swaroop Guntupalli, Guangyao Zhou, Kevin Patrick Murphy, Arthur Gretton, Arnaud Doucet
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu, Aoyama Tatsuya, Tomonari Tanaka, Akahane Satoshi, Hiroyuki Hanada, Noriaki Hashimoto, Taro Murayama [東京科学大学] [大阪大学], Hanju Lee, Shinya Kojima, Ichiro Takeuchi
Machine Learning
日本大学: 東京科学大学 / 名古屋工業大学 / 名古屋大学 / 大阪大学
2025 · ICML
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
Guangyi Liu, Suzan Iloglu, Michael Caldara, Joseph W Durham, Michael M. Zavlanos
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Distributionally Robust Policy Learning under Concept Drifts
Jingyuan Wang, Zhimei Ren, Ruohan Zhan, Zhengyuan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diverging Preferences: When do Annotators Disagree and do Models Know?
Michael Jq Zhang, Zhilin Wang, Jena D. Hwang, Yi Dong, Olivier Delalleau, Yejin Choi, Eunsol Choi, Xiang Ren, Valentina Pyatkin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Nguyen Nhat Minh To, Paul F R Wilson, Viet Nguyen, Mohamed Harmanani, Michael Cooper, Fahimeh Fooladgar, Purang Abolmaesumi, Parvin Mousavi, Rahul Krishnan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diversified Flow Matching with Translation Identifiability
Sagar Shrestha, Xiao Fu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity
Zhenglin Wan, Xingrui Yu, David Mark Bossens, Yueming Lyu, Qing Guo, Flint Xiaofeng Fan, Yew-Soon Ong, Ivor Tsang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
Michael S Yao, James Gee, Osbert Bastani
Machine Learning
日本大学: 関与なし（対象大学）