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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
AEQA-NAT : Adaptive End-to-end Quantization Alignment Training Framework for Non-autoregressive Machine Translation
Xiangyu Qu, Guojing Liu, Liang Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment
Yuqin Cao, Xiongkuo Min, Yixuan Gao, Wei Sun, Guangtao Zhai
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N
Tianyu Zhang, Andrew Robert Williams, Phillip Wozny, Kai-Hendrik Cohrs, Koen Ponse, Marco Jiralerspong, Soham Rajesh Phade, Sunil Srinivasa, Lu Li, Yang Zhang, Prateek Gupta, Erman Acar, Irina Rish, Yoshua Bengio, Stephan Zheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AKORN: Adaptive Knots generated Online for RegressioN splines
Sunil Madhow, Dheeraj Baby, Yu-Xiang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AKRMap: Adaptive Kernel Regression for Trustworthy Visualization of Cross-Modal Embeddings
Yilin Ye, Junchao Huang, Xingchen Zeng, Jiazhi Xia, Wei Zeng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ALMTokenizer: A Low-bitrate and Semantic-rich Audio Codec Tokenizer for Audio Language Modeling
Dongchao Yang, Songxiang Liu, Haohan Guo, Jiankun Zhao, Yuanyuan Wang, Helin Wang, Zeqian Ju, Xubo Liu, Xueyuan Chen, Xu Tan, Xixin Wu, Helen M. Meng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AMPO: Active Multi Preference Optimization for Self-play Preference Selection
Taneesh Gupta, Rahul Madhavan, Xuchao Zhang, Chetan Bansal, Saravan Rajmohan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
Myungsik Cho, Jongeui Park, Jeonghye Kim, Youngchul Sung
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
Arto Maranjyan, El Mehdi Saad, Peter Richtárik, Francesco Orabona
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AUTOCIRCUIT-RL: Reinforcement Learning-Driven LLM for Automated Circuit Topology Generation
Prashanth Vijayaraghavan, Luyao Shi, Ehsan Degan, Vandana Mukherjee, Xin Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
Shengbin Ye, Meng Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accelerated Diffusion Models via Speculative Sampling
Valentin De Bortoli, Alexandre Galashov, Arthur Gretton, Arnaud Doucet
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Gaurav Jain, Oren Pereg, Moshe Wasserblat, David Harel
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accelerating Large Language Model Reasoning via Speculative Search
Zhihai Wang, Jie Wang, Jilai Pan, Xilin Xia, Huiling Zhen, Mingxuan Yuan, Jianye Hao, Feng Wu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck, Philipp Stratmann, Andreas Wild, Sumit Bam Shrestha
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
Ze Cheng, Zhuoyu Li, Wang Xiaoqiang, Jianing Huang, Zhizhou Zhang, Zhongkai Hao, Hang Su
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach
Yang Xu, Vaneet Aggarwal
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accelerating Spectral Clustering under Fairness Constraints
Francesco Tonin, Alex Lambert, Johan Suykens, Volkan Cevher
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accelerating Unbiased LLM Evaluation via Synthetic Feedback
Zhaoyi Zhou, Yuda Song, Andrea Zanette
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accurate Identification of Communication Between Multiple Interacting Neural Populations
Belle Liu, Jacob Sacks, Matthew D. Golub
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Accurate and Efficient World Modeling with Masked Latent Transformers
Maxime Burchi, Radu Timofte
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Achieving Linear Speedup and Near-Optimal Complexity for Decentralized Optimization over Row-stochastic Networks
Liyuan Liang, Xinyi Chen, Gan Luo, Kun Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Action Dubber: Timing Audible Actions via Inflectional Flow
Wenlong Wan, Weiying Zheng, Tianyi Xiang, Guiqing Li, Shengfeng He
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Action-Constrained Imitation Learning
Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio, Wei Hung, Hung Yen Wu, Shao-Hua Sun, Ping-Chun Hsieh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Action-Dependent Optimality-Preserving Reward Shaping
Grant Collier Forbes, Jianxun Wang, Leonardo Villalobos-Arias, Arnav Jhala, David Roberts
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional
Sanjeev Raja, Martin Sipka, Michael Psenka, Tobias Kreiman, Michal Pavelka, Aditi S. Krishnapriyan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
Yupeng Hou, Jianmo Ni, Zhankui He, Noveen Sachdeva, Wang-Cheng Kang, Ed H. Chi, Julian Mcauley, Derek Zhiyuan Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Activation Space Interventions Can Be Transferred Between Large Language Models
Narmeen Fatimah Oozeer, Dhruv Nathawani, Nirmalendu Prakash, Michael Lan, Abir Harrasse, Amir Abdullah
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss
Sangyeon Park, Isaac Han, Seungwon Oh, Kyungjoong Kim
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Active Evaluation Acquisition for Efficient LLM Benchmarking
Yang Li, Jie Ma, Miguel Ballesteros, Yassine Benajiba, Graham Horwood
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Active Fine-Tuning of Multi-Task Policies
Marco Bagatella, Jonas Hübotter, Georg Martius, Andreas Krause
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations
Jason Qin, Hans-Hermann Wessels, Carlos Fernandez-Granda, Yuhan Hao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
Erica Zhang, Fangzhao Zhang, Mert Pilanci
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Active Learning with Selective Time-Step Acquisition for PDEs
Yegon Kim, Hyunsu Kim, Gyeonghoon Ko, Juho Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
Yunyi Shen, Hao Sun, Jean-Francois Ton
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Active Treatment Effect Estimation via Limited Samples
Zhiheng Zhang, Haoxiang Wang, Haoxuan Li, Zhouchen Lin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Active feature acquisition via explainability-driven ranking
Osman Berke Guney, Ketan Suhaas Saichandran, Karim Elzokm, Ziming Zhang, Vijaya B Kolachalama
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Actor-Critics Can Achieve Optimal Sample Efficiency
Kevin Tan, Wei Fan, Yuting Wei
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
Xinzhi Zhang, Hohei Chan, Deheng Ye, Yi Cai, Mengchen Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ad-Hoc Human-AI Coordination Challenge
Tin Dizdarević, Ravi Hammond, Tobias Gessler, Anisoara Calinescu, Jonathan Cook, Matteo Gallici, Andrei Lupu, Jakob Nicolaus Foerster
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AdaDecode: Accelerating LLM Decoding with Adaptive Layer Parallelism
Zhepei Wei, Wei-Lin Chen, Xinyu Zhu, Yu Meng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AdaSplash: Adaptive Sparse Flash Attention
Nuno Gonçalves, Marcos V Treviso, Andre Martins
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AdaWorld: Learning Adaptable World Models with Latent Actions
Shenyuan Gao, Siyuan Zhou, Yilun Du, Jun Zhang, Chuang Gan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
Jintao Tong, Ran Ma, Yixiong Zou, Guangyao Chen, Yuhua Li, Ruixuan Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adapting Precomputed Features for Efficient Graph Condensation
Yuan Li, Jun Hu, Zemin Liu, Bryan Hooi, Jia Chen, Bingsheng He
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation
Bohan Lyu, Yadi Cao, Duncan Watson-Parris, Leon Bergen, Taylor Berg-Kirkpatrick, Rose Yu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adapting to Evolving Adversaries with Regularized Continual Robust Training
Sihui Dai, Christian Cianfarani, Vikash Sehwag, Prateek Mittal, Arjun Bhagoji
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
Erchi Wang, Yuqing Zhu, Yu-Xiang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Data Collection for Robust Learning Across Multiple Distributions
Chengbo Zang, Mehmet Kerem Turkcan, Gil Zussman, Zoran Kostic, Javad Ghaderi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Elicitation of Latent Information Using Natural Language
Jimmy Wang, Thomas P Zollo, Richard Zemel, Hongseok Namkoong
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Estimation and Learning under Temporal Distribution Shift
Dheeraj Baby, Yifei Tang, Hieu Duy Nguyen, Yu-Xiang Wang, Rohit Pyati
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
Alessio Russo, Aldo Pacchiano
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Flow Matching for Resolving Small-Scale Physics
Stathi Fotiadis, Noah D Brenowitz, Tomas Geffner, Yair Cohen, Michael Pritchard, Arash Vahdat, Morteza Mardani
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection
Matteo Zecchin, Sangwoo Park, Osvaldo Simeone
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Localization of Knowledge Negation for Continual LLM Unlearning
Abudukelimu Wuerkaixi, Qizhou Wang, Sen Cui, Wutong Xu, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang
Machine Learning
日本大学: 東京大学
2025 · ICML
Adaptive Median Smoothing: Adversarial Defense for Unlearned Text-to-Image Diffusion Models at Inference Time
Xiaoxuan Han, Songlin Yang, Wei Wang, Yang Li, Jing Dong
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
Federico Errica, Henrik Christiansen, Viktor Zaverkin, Takashi Maruyama, Mathias Niepert, Francesco Alesiani
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Multi-prompt Contrastive Network for Few-shot Out-of-distribution Detection
Xiang Fang, Arvind Easwaran, Blaise Genest
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Partitioning Schemes for Optimistic Optimization
Raja Sunkara, Ardhendu Tripathy
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Sample Sharing for Multi Agent Linear Bandits
Hamza Cherkaoui, Merwan Barlier, Igor Colin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Self-improvement LLM Agentic System for ML Library Development
Genghan Zhang, Weixin Liang, Olivia Hsu, Kunle Olukotun
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive Sensitivity Analysis for Robust Augmentation against Natural Corruptions in Image Segmentation
Laura Yu Zheng, Wenjie Wei, Tony Wu, Jacob Clements, Shreelekha Revankar, Andre Harrison, Yu Shen, Ming Lin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adaptive kernel predictors from feature-learning infinite limits of neural networks
Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
Yuliang Liu, Junjie Lu, Chaofeng Qu, Zhaoling Chen, Zefan Cai, Jason Klein Liu, Chonghan Liu, Yunhui Xia, Li Zhao, Jiang Bian, Chuheng Zhang, Wei Shen, Zhouhan Lin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
Emiliano Penaloza, Tianyue H. Zhang, Laurent Charlin, Mateo Espinosa Zarlenga
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Joern-Henrik Jacobsen, Marco Cuturi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Aaron J Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Lucie Filippi, Mark Van Der Wilk
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adjustment for Confounding using Pre-Trained Representations
Rickmer Schulte, David Rügamer, Thomas Nagler
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AdvAgent: Controllable Blackbox Red-teaming on Web Agents
Chejian Xu, Mintong Kang, Jiawei Zhang, Zeyi Liao, Lingbo Mo, Mengqi Yuan, Huan Sun, Bo Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion Models
Yaopei Zeng, Yuanpu Cao, Bochuan Cao, Yurui Chang, Jinghui Chen, Lu Lin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
Davide Sartor, Alberto Sinigaglia, Gian Antonio Susto
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge
Hanglei Hu, Yingying Guo, Zhikang Chen, Sen Cui, Fei Wu, Kun Kuang, Min Zhang, Bo Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Combinatorial Semi-bandits with Graph Feedback
Yuxiao Wen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets
Wei Liu, Zhongyu Niu, Lang Gao, Zhiying Deng, Jun Wang, Haozhao Wang, Ruixuan Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Inception Backdoor Attacks against Reinforcement Learning
Ethan Rathbun, Alina Oprea, Christopher Amato
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Lukas Pirch, Felix Weissberg, Sebastian Baunsgaard, Thorsten Eisenhofer, Konrad Rieck
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian
Thomas Paniagua, Chinmay Savadikar, Tianfu Wu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Reasoning at Jailbreaking Time
Mahdi Sabbaghi, Paul Kassianik, George J. Pappas, Amin Karbasi, Hamed Hassani
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Robust Generalization of Graph Neural Networks
Chang Cao, Han Li, Yulong Wang, Rui Wu, Hong Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees
Yannis Montreuil, Axel Carlier, Lai Xing Ng, Wei Tsang Ooi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversarial Robustness via Deformable Convolution with Stochasticity
Yanxiang Ma, Zixuan Huang, Minjing Dong, Shan You, Chang Xu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Adversaries Can Misuse Combinations of Safe Models
Erik Jones, Anca Dragan, Jacob Steinhardt
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks
Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models
Zheng Lian, Haoyu Chen, Lan Chen, Haiyang Sun, Licai Sun, Yong Ren, Zebang Cheng, Bin Liu, Rui Liu, Xiaojiang Peng, Jiangyan Yi, Jianhua Tao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
AffinityFlow: Guided Flows for Antibody Affinity Maturation
Can Chen, Karla-Luise Herpoldt, Chenchao Zhao, Zichen Wang, Marcus D. Collins, Shang Shang, Ron Benson
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Agent Reviewers: Domain-specific Multimodal Agents with Shared Memory for Paper Review
Kai Lu, Shixiong Xu, Jinqiu Li, Kun Ding, Gaofeng Meng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Agent Workflow Memory
Zora Zhiruo Wang, Jiayuan Mao, Daniel Fried, Graham Neubig
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Agent-Centric Actor-Critic for Asynchronous Multi-Agent Reinforcement Learning
Whiyoung Jung, Sunghoon Hong, Deunsol Yoon, Kanghoon Lee, Woohyung Lim
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Agent-as-a-Judge: Evaluate Agents with Agents
Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Aggregation Buffer: Revisiting DropEdge with a New Parameter Block
Dooho Lee, Myeong Kong, Sagad Hamid, Cheonwoo Lee, Jaemin Yoo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
Rogelio A. Mancisidor, Robert Jenssen, Shujian Yu, Michael Kampffmeyer
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction
Yiheng Xu, Zekun Wang, Junli Wang, Dunjie Lu, Tianbao Xie, Amrita Saha, Doyen Sahoo, Tao Yu, Caiming Xiong
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Alberta Wells Dataset: Pinpointing Oil and Gas Wells from Satellite Imagery
Pratinav Seth, Michelle Lin, Brefo Dwamena Yaw, Jade Boutot, Mary Kang, David Rolnick
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Algorithm Development in Neural Networks: Insights from the Streaming Parity Task
Loek Van Rossem, Andrew M Saxe
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Algorithmic Recourse for Long-Term Improvement
Kentaro Kanamori, Ken Kobayashi, Satoshi Hara, Takuya Takagi
Machine Learning
日本大学: 東京科学大学 / 電気通信大学
2025 · ICML
Algorithms and Hardness for Active Learning on Graphs
Vincent Cohen-Addad, Silvio Lattanzi, Simon Meierhans
Machine Learning
日本大学: 関与なし（対象大学）