ICML

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Machine Learning

2024 · 2,610 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。

2024 · ICML
MaSS: Multi-attribute Selective Suppression for Utility-preserving Data Transformation from an Information-theoretic Perspective
Yizhuo Chen, Chun-Fu Chen, Hsiang Hsu, Shaohan Hu, Marco Pistoia, Tarek F. Abdelzaher
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning
Zhuo Huang, Chang Liu, Yinpeng Dong, Hang Su, Shibao Zheng, Tongliang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition
Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions
Kai Zhang, Yi Luan, Hexiang Hu, Kenton Lee, Siyuan Qiao, Wenhu Chen, Yu Su, Ming-Wei Chang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion
Di Chang, Yichun Shi, Quankai Gao, Hongyi Xu, Jessica Fu, Guoxian Song, Qing Yan, Yizhe Zhu, Xiao Yang, Mohammad Soleymani
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Magicoder: Empowering Code Generation with OSS-Instruct
Yuxiang Wei, Zhe Wang, Jiawei Liu, Yifeng Ding, Lingming Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Major-Minor Mean Field Multi-Agent Reinforcement Learning
Kai Cui, Christian Fabian, Anam Tahir, Heinz Koeppl
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Make-A-Shape: a Ten-Million-scale 3D Shape Model
Ka-Hei Hui, Aditya Sanghi, Arianna Rampini, Kamal Rahimi Malekshan, Zhengzhe Liu, Hooman Shayani, Chi-Wing Fu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
Max Dupre La Tour, Monika Henzinger, David Saulpic
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution
Eslam Zaher, Maciej Trzaskowski, Quan Nguyen, Fred Roosta
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mapping the Multiverse of Latent Representations
Jeremy Wayland, Corinna Coupette, Bastian Rieck
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Masked Face Recognition with Generative-to-Discriminative Representations
Shiming Ge, Weijia Guo, Chenyu Li, Zhang Junzheng, Yong Li, Dan Zeng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning
Jiachen Li, Qiaozi Gao, Michael Johnston, Xiaofeng Gao, Xuehai He, Hangjie Shi, Suhaila Shakiah, Reza Ghanadan, William Yang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs
Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, Bin Cui
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
Yannik Mahlau, Frederik Schubert, Bodo Rosenhahn
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MathScale: Scaling Instruction Tuning for Mathematical Reasoning
Zhengyang Tang, Xingxing Zhang, Benyou Wang, Furu Wei
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Matrix Information Theory for Self-Supervised Learning
Yifan Zhang, Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Matroid Semi-Bandits in Sublinear Time
Ruo-Chun Tzeng, Naoto Ohsaka, Kaito Ariu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MaxMin-RLHF: Alignment with Diverse Human Preferences
Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Dinesh Manocha, Furong Huang, Amrit Bedi, Mengdi Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mean Estimation in the Add-Remove Model of Differential Privacy
Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning
Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki
Machine Learning
日本大学: 東京大学
2024 · ICML
Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
Shokichi Takakura, Taiji Suzuki
Machine Learning
日本大学: 東京大学
2024 · ICML
Mean-field Chaos Diffusion Models
Sungwoo Park, Dongjun Kim, Ahmed Alaa
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mean-field Underdamped Langevin Dynamics and its Spacetime Discretization
Qiang Fu, Ashia Camage Wilson
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Measures of diversity and space-filling designs for categorical data
Cedric Malherbe, Emilio Domı́nguez-Sánchez, Merwan Barlier, Igor Colin, Haitham Bou Ammar, Tom Diethe
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Measuring Stochastic Data Complexity with Boltzmann Influence Functions
Nathan Hoyen Ng, Roger Baker Grosse, Marzyeh Ghassemi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mechanistic Design and Scaling of Hybrid Architectures
Michael Poli, Armin W Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Re, Ce Zhang, Stefano Massaroli
Machine Learning
日本大学: 東京大学
2024 · ICML
Mechanistic Neural Networks for Scientific Machine Learning
Adeel Pervez, Francesco Locatello, Stratis Gavves
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads
Tianle Cai, Yuhong Li, Zhengyang Geng, Hongwu Peng, Jason D. Lee, Deming Chen, Tri Dao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Membership Inference Attacks on Diffusion Models via Quantile Regression
Shuai Tang, Steven Wu, Sergul Aydore, Michael Kearns, Aaron Roth
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Memoria: Resolving Fateful Forgetting Problem through Human-Inspired Memory Architecture
Sangjun Park, Jinyeong Bak
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Memorization Through the Lens of Curvature of Loss Function Around Samples
Isha Garg, Deepak Ravikumar, Kaushik Roy
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Memory Consolidation Enables Long-Context Video Understanding
Ivana Balazevic, Yuge Shi, Pinelopi Papalampidi, Rahma Chaabouni, Skanda Koppula, Olivier J Henaff
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Memory Efficient Neural Processes via Constant Memory Attention Block
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning
Shibo Jie, Yehui Tang, Ning Ding, Zhi-Hong Deng, Kai Han, Yunhe Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Merging Multi-Task Models via Weight-Ensembling Mixture of Experts
Anke Tang, Li Shen, Yong Luo, Nan Yin, Lefei Zhang, Dacheng Tao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Meta Evidential Transformer for Few-Shot Open-Set Recognition
Hitesh Sapkota, Krishna Prasad Neupane, Qi Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
Jonas Schweisthal, Dennis Frauen, Mihaela Van Der Schaar, Stefan Feuerriegel
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning
Tengye Xu, Zihao Li, Qinyuan Ren
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mimicking Better by Matching the Approximate Action Distribution
Joao Candido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mind the Boundary: Coreset Selection via Reconstructing the Decision Boundary
Shuo Yang, Zhe Cao, Sheng Guo, Ruiheng Zhang, Ping Luo, Shengping Zhang, Liqiang Nie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Data
Paul Steven Scotti, Mihir Tripathy, Cesar Torrico, Reese Kneeland, Tong Chen, Ashutosh Narang, Charan Santhirasegaran, Jonathan Xu, Thomas Naselaris, Kenneth A. Norman, Tanishq Mathew Abraham
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value
Young Wu, Jeremy Mcmahan, Yiding Chen, Yudong Chen, Jerry Zhu, Qiaomin Xie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
Kaihong Zhang, Heqi Yin, Feng Liang, Jingbo Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Minimizing $f$-Divergences by Interpolating Velocity Fields
Song Liu, Jiahao Yu, Jack Simons, Mingxuan Yi, Mark Beaumont
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Minimum Norm Interpolation Meets The Local Theory of Banach Spaces
Gil Kur, Pedro Abdalla, Pierre Bizeul, Fanny Yang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Minimum-Norm Interpolation Under Covariate Shift
Neil Rohit Mallinar, Austin Zane, Spencer Frei, Bin Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization
Yichen Wu, Hong Wang, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mitigating Label Noise on Graphs via Topological Sample Selection
Yuhao Wu, Jiangchao Yao, Xiaobo Xia, Jun Yu, Ruxin Wang, Bo Han, Tongliang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
Moonjeong Park, Jaeseung Heo, Dongwoo Kim
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
Zhenlong Liu, Lei Feng, Huiping Zhuang, Xiaofeng Cao, Hongxin Wei
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mixtures of Experts Unlock Parameter Scaling for Deep RL
Johan Samir Obando Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MoMo: Momentum Models for Adaptive Learning Rates
Fabian Schaipp, Ruben Ohana, Michael Eickenberg, Aaron Defazio, Robert M. Gower
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers
Zhiyu Yao, Jian Wang, Haixu Wu, Jingdong Wang, Mingsheng Long
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases
Zechun Liu, Changsheng Zhao, Forrest Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Model Alignment as Prospect Theoretic Optimization
Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, Douwe Kiela
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Model Assessment and Selection under Temporal Distribution Shift
Elise Han, Chengpiao Huang, Kaizheng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
Didi Zhu, Zhongyisun Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Chao Wu, Kun Kuang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Model-Based Minimum Bayes Risk Decoding for Text Generation
Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
Jiawei Huang, Niao He, Andreas Krause
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Model-Free Robust $φ$-Divergence Reinforcement Learning Using Both Offline and Online Data
Kishan Panaganti, Adam Wierman, Eric Mazumdar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Model-based Reinforcement Learning for Confounded POMDPs
Mao Hong, Zhengling Qi, Yanxun Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Model-based Reinforcement Learning for Parameterized Action Spaces
Renhao Zhang, Haotian Fu, Yilin Miao, George Konidaris
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Modeling Caption Diversity in Contrastive Vision-Language Pretraining
Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mido Assran, Andrew Gordon Wilson, Aaron Courville, Nicolas Ballas
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Modeling Language Tokens as Functionals of Semantic Fields
Zhengqi Pei, Anran Zhang, Shuhui Wang, Qingming Huang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Modelling Microbial Communities with Graph Neural Networks
Albane Ruaud, Cansu Sancaktar, Marco Bagatella, Christoph Ratzke, Georg Martius
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
Md Musfiqur Rahman, Murat Kocaoglu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective
Junwei Yang, Kangjie Zheng, Siyu Long, Zaiqing Nie, Ming Zhang, Xinyu Dai, Wei-Ying Ma, Hao Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
Yanru Qu, Keyue Qiu, Yuxuan Song, Jingjing Gong, Jiawei Han, Mingyue Zheng, Hao Zhou, Wei-Ying Ma
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Mollification Effects of Policy Gradient Methods
Tao Wang, Sylvia Lee Herbert, Sicun Gao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning
Long Qian, Juncheng Li, Yu Wu, Yaobo Ye, Hao Fei, Tat-Seng Chua, Yueting Zhuang, Siliang Tang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Momentum Particle Maximum Likelihood
Jen Ning Lim, Juan Kuntz, Samuel Power, Adam Michael Johansen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
Han Wang, Sihong He, Zhili Zhang, Fei Miao, James Anderson
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews
Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, Daniel Mcfarland, James Y. Zou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Monotone Individual Fairness
Yahav Bechavod
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Monotone, Bi-Lipschitz, and Polyak-Łojasiewicz Networks
Ruigang Wang, Krishnamurthy Dj Dvijotham, Ian Manchester
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning
Kaiwen Wang, Owen Oertell, Alekh Agarwal, Nathan Kallus, Wen Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
Hossein Zakerinia, Amin Behjati, Christoph H. Lampert
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-Loop and Hessian-Free Solution Strategy
Risheng Liu, Zhu Liu, Wei Yao, Shangzhi Zeng, Jin Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Nianzu Yang, Kaipeng Zeng, Haotian Lu, Yexin Wu, Zexin Yuan, Danni Chen, Shengdian Jiang, Jiaxiang Wu, Yimin Wang, Junchi Yan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
Riqiang Gao, Florin-Cristian Ghesu, Simon Arberet, Shahab Basiri, Esa Kuusela, Martin Kraus, Dorin Comaniciu, Ali Kamen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing
Amutheezan Sivagnanam, Ava Pettet, Hunter Lee, Ayan Mukhopadhyay, Abhishek Dubey, Aron Laszka
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Factor Adaptive Vision Selection for Egocentric Video Question Answering
Haoyu Zhang, Meng Liu, Zixin Liu, Xuemeng Song, Yaowei Wang, Liqiang Nie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
Ruijia Niu, Dongxia Wu, Kai Kim, Yian Ma, Duncan Watson-Parris, Rose Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning
Yuxuan Bian, Xuan Ju, Jiangtong Li, Zhijian Xu, Dawei Cheng, Qiang Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
Weihan Li, Chengrui Li, Yule Wang, Anqi Wu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Sender Persuasion: A Computational Perspective
Safwan Hossain, Tonghan Wang, Tao Lin, Yiling Chen, David C. Parkes, Haifeng Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Source Conformal Inference Under Distribution Shift
Yi Liu, Alexander Levis, Sharon-Lise Normand, Larry Han
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing
Hongbin Pei, Yu Li, Huiqi Deng, Jingxin Hai, Pinghui Wang, Jie Ma, Jing Tao, Yuheng Xiong, Xiaohong Guan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-View Clustering by Inter-cluster Connectivity Guided Reward
Hao Dai, Yang Liu, Peng Su, Hecheng Cai, Shudong Huang, Jiancheng Lv
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-View Stochastic Block Models
Vincent Cohen-Addad, Tommaso D’Orsi, Silvio Lattanzi, Rajai Nasser
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-group Learning for Hierarchical Groups
Samuel Deng, Daniel Hsu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning
Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MultiMax: Sparse and Multi-Modal Attention Learning
Yuxuan Zhou, Mario Fritz, Margret Keuper
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multicalibration for Confidence Scoring in LLMs
Gianluca Detommaso, Martin Andres Bertran, Riccardo Fogliato, Aaron Roth
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multigroup Robustness
Lunjia Hu, Charlotte Peale, Judy Hanwen Shen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multimodal Prototyping for cancer survival prediction
Andrew H. Song, Richard J. Chen, Guillaume Jaume, Anurag Jayant Vaidya, Alexander Baras, Faisal Mahmood
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multiplicative Weights Update, Area Convexity and Random Coordinate Descent for Densest Subgraph Problems
Ta Duy Nguyen, Alina Ene
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains
Steven Wilkins-Reeves, Xu Chen, Qi Ma, Christine Agarwal, Aude Hofleitner
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Multiply-Robust Causal Change Attribution
Victor Quintas-Martinez, Mohammad Taha Bahadori, Eduardo Santiago, Jeff Mu, David Heckerman
Machine Learning
日本大学: 関与なし（対象大学）