Conferences · eligible papers

ICML

2021–2025 確定版

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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。

  1. 2024 · ICML

    Cluster-Aware Similarity Diffusion for Instance Retrieval

    Jifei Luo, Hantao Yao, Changsheng Xu

    Machine Learning

    日本大学: 関与なし(対象大学)

  2. 2024 · ICML

    Clustered Federated Learning via Gradient-based Partitioning

    Heasung Kim, Hyeji Kim, Gustavo De Veciana

    Machine Learning

    日本大学: 関与なし(対象大学)

  3. 2024 · ICML

    CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations

    Jules Berman, Benjamin Peherstorfer

    Machine Learning

    日本大学: 関与なし(対象大学)

  4. 2024 · ICML

    Coactive Learning for Large Language Models using Implicit User Feedback

    Aaron David Tucker, Kianté Brantley, Adam Cahall, Thorsten Joachims

    Machine Learning

    日本大学: 関与なし(対象大学)

  5. 2024 · ICML

    Coarse-To-Fine Tensor Trains for Compact Visual Representations

    Sebastian Bugge Loeschcke, Dan Wang, Christian Munklinde Leth-Espensen, Serge Belongie, Michael Kastoryano, Sagie Benaim

    Machine Learning

    日本大学: 関与なし(対象大学)

  6. 2024 · ICML

    Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models

    Qitan Lv, Jie Wang, Hanzhu Chen, Bin Li, Yongdong Zhang, Feng Wu

    Machine Learning

    日本大学: 関与なし(対象大学)

  7. 2024 · ICML

    Code as Reward: Empowering Reinforcement Learning with VLMs

    David Venuto, Mohammad Sami Nur Islam, Martin Klissarov, Doina Precup, Sherry Yang, Ankit Anand

    Machine Learning

    日本大学: 関与なし(対象大学)

  8. 2024 · ICML

    CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay

    Natasha Butt, Blazej Manczak, Auke Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen

    Machine Learning

    日本大学: 関与なし(対象大学)

  9. 2024 · ICML

    Codebook Features: Sparse and Discrete Interpretability for Neural Networks

    Alex Tamkin, Mohammad Taufeeque, Noah Goodman

    Machine Learning

    日本大学: 関与なし(対象大学)

  10. 2024 · ICML

    CogBench: a large language model walks into a psychology lab

    Julian Coda-Forno, Marcel Binz, Jane X Wang, Eric Schulz

    Machine Learning

    日本大学: 関与なし(対象大学)

  11. 2024 · ICML

    CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding

    Kaiyuan Chen, Xingzhuo Guo, Yu Zhang, Jianmin Wang, Mingsheng Long

    Machine Learning

    日本大学: 関与なし(対象大学)

  12. 2024 · ICML

    Collaborative Heterogeneous Causal Inference Beyond Meta-analysis

    Tianyu Guo, Sai Praneeth Karimireddy, Michael Jordan

    Machine Learning

    日本大学: 関与なし(対象大学)

  13. 2024 · ICML

    Collaborative Learning with Different Labeling Functions

    Yuyang Deng, Mingda Qiao

    Machine Learning

    日本大学: 関与なし(対象大学)

  14. 2024 · ICML

    Collage: Light-Weight Low-Precision Strategy for LLM Training

    Tao Yu, Gaurav Gupta, Karthick Gopalswamy, Amith R Mamidala, Hao Zhou, Jeffrey Huynh, Youngsuk Park, Ron Diamant, Anoop Deoras, Luke Huan

    Machine Learning

    日本大学: 関与なし(対象大学)

  15. 2024 · ICML

    Collapse-Aware Triplet Decoupling for Adversarially Robust Image Retrieval

    Qiwei Tian, Chenhao Lin, Zhengyu Zhao, Qian Li, Chao Shen

    Machine Learning

    日本大学: 関与なし(対象大学)

  16. 2024 · ICML

    Collective Certified Robustness against Graph Injection Attacks

    Yuni Lai, Bailin Pan, Kaihuang Chen, Yancheng Yuan, Kai Zhou

    Machine Learning

    日本大学: 関与なし(対象大学)

  17. 2024 · ICML

    Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better

    Vicente Balmaseda, Ying Xu, Yixin Cao, Nate Veldt

    Machine Learning

    日本大学: 関与なし(対象大学)

  18. 2024 · ICML

    Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond

    Xutong Liu, Siwei Wang, Jinhang Zuo, Han Zhong, Xuchuang Wang, Zhiyong Wang, Shuai Li, Mohammad Hajiesmaili, John C.S. Lui, Wei Chen

    Machine Learning

    日本大学: 関与なし(対象大学)

  19. 2024 · ICML

    Combining Experimental and Historical Data for Policy Evaluation

    Ting Li, Chengchun Shi, Qianglin Wen, Yang Sui, Yongli Qin, Chunbo Lai, Hongtu Zhu

    Machine Learning

    日本大学: 関与なし(対象大学)

  20. 2024 · ICML

    Community-Invariant Graph Contrastive Learning

    Shiyin Tan, Dongyuan Li, Renhe Jiang, Ying Zhang, Manabu Okumura

    Machine Learning

    日本大学: 東京科学大学 / 東京大学

  21. 2024 · ICML

    Compact Optimality Verification for Optimization Proxies

    Wenbo Chen, Haoruo Zhao, Mathieu Tanneau, Pascal Van Hentenryck

    Machine Learning

    日本大学: 関与なし(対象大学)

  22. 2024 · ICML

    Comparing Graph Transformers via Positional Encodings

    Mitchell Black, Zhengchao Wan, Gal Mishne, Amir Nayyeri, Yusu Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  23. 2024 · ICML

    CompeteAI: Understanding the Competition Dynamics of Large Language Model-based Agents

    Qinlin Zhao, Jindong Wang, Yixuan Zhang, Yiqiao Jin, Kaijie Zhu, Hao Chen, Xing Xie

    Machine Learning

    日本大学: 関与なし(対象大学)

  24. 2024 · ICML

    Completing Visual Objects via Bridging Generation and Segmentation

    Xiang Li, Yinpeng Chen, Chung-Ching Lin, Hao Chen, Kai Hu, Rita Singh, Bhiksha Raj, Lijuan Wang, Zicheng Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  25. 2024 · ICML

    Complexity Matters: Feature Learning in the Presence of Spurious Correlations

    Guanwen Qiu, Da Kuang, Surbhi Goel

    Machine Learning

    日本大学: 関与なし(対象大学)

  26. 2024 · ICML

    Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks

    Rahul Ramesh, Ekdeep Singh Lubana, Mikail Khona, Robert P. Dick, Hidenori Tanaka

    Machine Learning

    日本大学: 関与なし(対象大学)

  27. 2024 · ICML

    Compositional Curvature Bounds for Deep Neural Networks

    Taha Entesari, Sina Sharifi, Mahyar Fazlyab

    Machine Learning

    日本大学: 関与なし(対象大学)

  28. 2024 · ICML

    Compositional Few-Shot Class-Incremental Learning

    Yixiong Zou, Shanghang Zhang, Haichen Zhou, Yuhua Li, Ruixuan Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  29. 2024 · ICML

    Compositional Image Decomposition with Diffusion Models

    Jocelin Su, Nan Liu, Yanbo Wang, Joshua B. Tenenbaum, Yilun Du

    Machine Learning

    日本大学: 関与なし(対象大学)

  30. 2024 · ICML

    Compositional Text-to-Image Generation with Dense Blob Representations

    Weili Nie, Sifei Liu, Morteza Mardani, Chao Liu, Benjamin Eckart, Arash Vahdat

    Machine Learning

    日本大学: 関与なし(対象大学)

  31. 2024 · ICML

    Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach

    Zhihao Li, Yufei Wang, Alex Kot, Bihan Wen

    Machine Learning

    日本大学: 関与なし(対象大学)

  32. 2024 · ICML

    Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation

    Can Yaras, Peng Wang, Laura Balzano, Qing Qu

    Machine Learning

    日本大学: 関与なし(対象大学)

  33. 2024 · ICML

    Compressing Large Language Models by Joint Sparsification and Quantization

    Jinyang Guo, Jianyu Wu, Zining Wang, Jiaheng Liu, Ge Yang, Yifu Ding, Ruihao Gong, Haotong Qin, Xianglong Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  34. 2024 · ICML

    Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth

    Kevin Kögler, Aleksandr Shevchenko, Hamed Hassani, Marco Mondelli

    Machine Learning

    日本大学: 関与なし(対象大学)

  35. 2024 · ICML

    Compute Better Spent: Replacing Dense Layers with Structured Matrices

    Shikai Qiu, Andres Potapczynski, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson

    Machine Learning

    日本大学: 関与なし(対象大学)

  36. 2024 · ICML

    ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models

    Rohan Wadhawan, Hritik Bansal, Kai-Wei Chang, Nanyun Peng

    Machine Learning

    日本大学: 関与なし(対象大学)

  37. 2024 · ICML

    Concentration Inequalities for General Functions of Heavy-Tailed Random Variables

    Shaojie Li, Yong Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  38. 2024 · ICML

    Conditional Common Entropy for Instrumental Variable Testing and Partial Identification

    Ziwei Jiang, Murat Kocaoglu

    Machine Learning

    日本大学: 関与なし(対象大学)

  39. 2024 · ICML

    Conditional Language Learning with Context

    Xiao Zhang, Miao Li, Ji Wu

    Machine Learning

    日本大学: 関与なし(対象大学)

  40. 2024 · ICML

    Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations

    Henrik Schopmans, Pascal Friederich

    Machine Learning

    日本大学: 関与なし(対象大学)

  41. 2024 · ICML

    Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation

    Yididiya Y. Nadew, Xuhui Fan, Christopher John Quinn

    Machine Learning

    日本大学: 関与なし(対象大学)

  42. 2024 · ICML

    Confidence Aware Inverse Constrained Reinforcement Learning

    Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart

    Machine Learning

    日本大学: 関与なし(対象大学)

  43. 2024 · ICML

    Confidence-aware Contrastive Learning for Selective Classification

    Yu-Chang Wu, Shen-Huan Lyu, Haopu Shang, Xiangyu Wang, Chao Qian

    Machine Learning

    日本大学: 関与なし(対象大学)

  44. 2024 · ICML

    Configurable Mirror Descent: Towards a Unification of Decision Making

    Pengdeng Li, Shuxin Li, Chang Yang, Xinrun Wang, Shuyue Hu, Xiao Huang, Hau Chan, Bo An

    Machine Learning

    日本大学: 関与なし(対象大学)

  45. 2024 · ICML

    Conformal Prediction Sets Improve Human Decision Making

    Jesse C. Cresswell, Yi Sui, Bhargava Kumar, Noël Vouitsis

    Machine Learning

    日本大学: 関与なし(対象大学)

  46. 2024 · ICML

    Conformal Prediction for Deep Classifier via Label Ranking

    Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei

    Machine Learning

    日本大学: 関与なし(対象大学)

  47. 2024 · ICML

    Conformal Prediction with Learned Features

    Shayan Kiyani, George J. Pappas, Hamed Hassani

    Machine Learning

    日本大学: 関与なし(対象大学)

  48. 2024 · ICML

    Conformal Predictions under Markovian Data

    Frédéric Zheng, Alexandre Proutiere

    Machine Learning

    日本大学: 関与なし(対象大学)

  49. 2024 · ICML

    Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)

    Drew Prinster, Samuel Don Stanton, Anqi Liu, Suchi Saria

    Machine Learning

    日本大学: 関与なし(対象大学)

  50. 2024 · ICML

    Conformal prediction for multi-dimensional time series by ellipsoidal sets

    Chen Xu, Hanyang Jiang, Yao Xie

    Machine Learning

    日本大学: 関与なし(対象大学)

  51. 2024 · ICML

    Conformalized Adaptive Forecasting of Heterogeneous Trajectories

    Yanfei Zhou, Lars Lindemann, Matteo Sesia

    Machine Learning

    日本大学: 関与なし(対象大学)

  52. 2024 · ICML

    Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration

    Shi-Ang Qi, Yakun Yu, Russell Greiner

    Machine Learning

    日本大学: 関与なし(対象大学)

  53. 2024 · ICML

    Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases

    Ziyi Zhang, Sen Zhang, Yibing Zhan, Yong Luo, Yonggang Wen, Dacheng Tao

    Machine Learning

    日本大学: 関与なし(対象大学)

  54. 2024 · ICML

    Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations

    Helen Qu, Sang Michael Xie

    Machine Learning

    日本大学: 関与なし(対象大学)

  55. 2024 · ICML

    Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models

    Zhengbo Wang, Jian Liang, Ran He, Zilei Wang, Tieniu Tan

    Machine Learning

    日本大学: 関与なし(対象大学)

  56. 2024 · ICML

    Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?

    Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou, Ludwig Bothmann, Bernd Bischl, David Rügamer

    Machine Learning

    日本大学: 関与なし(対象大学)

  57. 2024 · ICML

    Consistent Adversarially Robust Linear Classification: Non-Parametric Setting

    Elvis Dohmatob

    Machine Learning

    日本大学: 関与なし(対象大学)

  58. 2024 · ICML

    Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data

    Giannis Daras, Alex Dimakis, Constantinos Costis Daskalakis

    Machine Learning

    日本大学: 関与なし(対象大学)

  59. 2024 · ICML

    Consistent Long-Term Forecasting of Ergodic Dynamical Systems

    Vladimir R Kostic, Karim Lounici, Prune Inzerilli, Pietro Novelli, Massimiliano Pontil

    Machine Learning

    日本大学: 関与なし(対象大学)

  60. 2024 · ICML

    Consistent Submodular Maximization

    Paul Duetting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam

    Machine Learning

    日本大学: 関与なし(対象大学)

  61. 2024 · ICML

    Constrained Ensemble Exploration for Unsupervised Skill Discovery

    Chenjia Bai, Rushuai Yang, Qiaosheng Zhang, Kang Xu, Yi Chen, Ting Xiao, Xuelong Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  62. 2024 · ICML

    Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics

    Haoyang Zheng, Hengrong Du, Qi Feng, Wei Deng, Guang Lin

    Machine Learning

    日本大学: 関与なし(対象大学)

  63. 2024 · ICML

    Constrained Reinforcement Learning Under Model Mismatch

    Zhongchang Sun, Sihong He, Fei Miao, Shaofeng Zou

    Machine Learning

    日本大学: 関与なし(対象大学)

  64. 2024 · ICML

    ContPhy: Continuum Physical Concept Learning and Reasoning from Videos

    Zhicheng Zheng, Xin Yan, Zhenfang Chen, Jingzhou Wang, Qin Zhi Eddie Lim, Joshua B. Tenenbaum, Chuang Gan

    Machine Learning

    日本大学: 関与なし(対象大学)

  65. 2024 · ICML

    Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data

    Wenxi Lv, Qinliang Su, Hai Wan, Hongteng Xu, Wenchao Xu

    Machine Learning

    日本大学: 関与なし(対象大学)

  66. 2024 · ICML

    Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design

    Leo Klarner, Tim G. J. Rudner, Garrett M Morris, Charlotte Deane, Yee Whye Teh

    Machine Learning

    日本大学: 関与なし(対象大学)

  67. 2024 · ICML

    Contextual Feature Selection with Conditional Stochastic Gates

    Ram Dyuthi Sristi, Ofir Lindenbaum, Shira Lifshitz, Maria Lavzin, Jackie Schiller, Gal Mishne, Hadas Benisty

    Machine Learning

    日本大学: 関与なし(対象大学)

  68. 2024 · ICML

    Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning

    Jannik Deuschel, Caleb Ellington, Yingtao Luo, Ben Lengerich, Pascal Friederich, Eric P. Xing

    Machine Learning

    日本大学: 関与なし(対象大学)

  69. 2024 · ICML

    Continuous Treatment Effects with Surrogate Outcomes

    Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward Kennedy

    Machine Learning

    日本大学: 関与なし(対象大学)

  70. 2024 · ICML

    Contrasting Multiple Representations with the Multi-Marginal Matching Gap

    Zoe Piran, Michal Klein, James Thornton, Marco Cuturi

    Machine Learning

    日本大学: 関与なし(対象大学)

  71. 2024 · ICML

    Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources

    Meng Xia, Jonathan Wilson, Benjamin Goldstein, Ricardo Henao

    Machine Learning

    日本大学: 関与なし(対象大学)

  72. 2024 · ICML

    Contrastive Predict-and-Search for Mixed Integer Linear Programs

    Taoan Huang, Aaron M Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina

    Machine Learning

    日本大学: 関与なし(対象大学)

  73. 2024 · ICML

    Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

    Haoran Xu, Amr Sharaf, Yunmo Chen, Weiting Tan, Lingfeng Shen, Benjamin Van Durme, Kenton Murray, Young Jin Kim

    Machine Learning

    日本大学: 関与なし(対象大学)

  74. 2024 · ICML

    Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning

    Xiaoyu Wen, Chenjia Bai, Kang Xu, Xudong Yu, Yang Zhang, Xuelong Li, Zhen Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  75. 2024 · ICML

    Controllable Prompt Tuning For Balancing Group Distributional Robustness

    Hoang Phan, Andrew Gordon Wilson, Qi Lei

    Machine Learning

    日本大学: 関与なし(対象大学)

  76. 2024 · ICML

    Controlled Decoding from Language Models

    Sidharth Mudgal, Jong Lee, Harish Ganapathy, Yaguang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Trevor Strohman, Jilin Chen, Alex Beutel, Ahmad Beirami

    Machine Learning

    日本大学: 関与なし(対象大学)

  77. 2024 · ICML

    Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning

    Matteo Bettini, Ryan Kortvelesy, Amanda Prorok

    Machine Learning

    日本大学: 関与なし(対象大学)

  78. 2024 · ICML

    ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

    Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  79. 2024 · ICML

    Convergence Guarantees for the DeepWalk Embedding on Block Models

    Christopher Harker, Aditya Bhaskara

    Machine Learning

    日本大学: 関与なし(対象大学)

  80. 2024 · ICML

    Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms

    Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu

    Machine Learning

    日本大学: 関与なし(対象大学)

  81. 2024 · ICML

    Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point

    David Martı́nez-Rubio, Christophe Roux, Sebastian Pokutta

    Machine Learning

    日本大学: 関与なし(対象大学)

  82. 2024 · ICML

    Convergence of Online Learning Algorithm for a Mixture of Multiple Linear Regressions

    Yujing Liu, Zhixin Liu, Lei Guo

    Machine Learning

    日本大学: 関与なし(対象大学)

  83. 2024 · ICML

    Convergence of Some Convex Message Passing Algorithms to a Fixed Point

    Vaclav Voracek, Tomas Werner

    Machine Learning

    日本大学: 関与なし(対象大学)

  84. 2024 · ICML

    Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption

    Itamar Zimerman, Moran Baruch, Nir Drucker, Gilad Ezov, Omri Soceanu, Lior Wolf

    Machine Learning

    日本大学: 関与なし(対象大学)

  85. 2024 · ICML

    Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time

    Sungyoon Kim, Mert Pilanci

    Machine Learning

    日本大学: 関与なし(対象大学)

  86. 2024 · ICML

    Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning

    Charles Andrew Dickens, Changyu Gao, Connor Pryor, Stephen Wright, Lise Getoor

    Machine Learning

    日本大学: 関与なし(対象大学)

  87. 2024 · ICML

    Cooperative Graph Neural Networks

    Ben Finkelshtein, Xingyue Huang, Michael M. Bronstein, Ismail Ilkan Ceylan

    Machine Learning

    日本大学: 関与なし(対象大学)

  88. 2024 · ICML

    Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation

    Michelle Pan, Mariah L Schrum, Vivek Myers, Erdem Biyik, Anca Dragan

    Machine Learning

    日本大学: 関与なし(対象大学)

  89. 2024 · ICML

    Copula-Nested Spectral Kernel Network

    Jinyue Tian, Hui Xue, Yanfang Xue, Pengfei Fang

    Machine Learning

    日本大学: 関与なし(対象大学)

  90. 2024 · ICML

    Copyright Traps for Large Language Models

    Matthieu Meeus, Igor Shilov, Manuel Faysse, Yves-Alexandre De Montjoye

    Machine Learning

    日本大学: 関与なし(対象大学)

  91. 2024 · ICML

    Coresets for Multiple $\ell_p$ Regression

    David Woodruff, Taisuke Yasuda

    Machine Learning

    日本大学: 関与なし(対象大学)

  92. 2024 · ICML

    Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder

    Yiyang Ma, Wenhan Yang, Jiaying Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  93. 2024 · ICML

    Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning

    Biao Liu, Ning Xu, Xiangyu Fang, Xin Geng

    Machine Learning

    日本大学: 関与なし(対象大学)

  94. 2024 · ICML

    CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks

    Shashank Agnihotri, Steffen Jung, Margret Keuper

    Machine Learning

    日本大学: 関与なし(対象大学)

  95. 2024 · ICML

    Counterfactual Image Editing

    Yushu Pan, Elias Bareinboim

    Machine Learning

    日本大学: 関与なし(対象大学)

  96. 2024 · ICML

    Counterfactual Metarules for Local and Global Recourse

    Tom Bewley, Salim I. Amoukou, Saumitra Mishra, Daniele Magazzeni, Manuela Veloso

    Machine Learning

    日本大学: 関与なし(対象大学)

  97. 2024 · ICML

    Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training

    Ming-Kun Xie, Jia-Hao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

    Machine Learning

    日本大学: 東京大学

  98. 2024 · ICML

    Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation

    Danny Halawi, Alexander Wei, Eric Wallace, Tony Tong Wang, Nika Haghtalab, Jacob Steinhardt

    Machine Learning

    日本大学: 関与なし(対象大学)

  99. 2024 · ICML

    Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning

    Michael Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew Thomas Jackson, Samuel Coward, Jakob Nicolaus Foerster

    Machine Learning

    日本大学: 関与なし(対象大学)

  100. 2024 · ICML

    Creative Text-to-Audio Generation via Synthesizer Programming

    Manuel Cherep, Nikhil Singh, Jessica Shand

    Machine Learning

    日本大学: 関与なし(対象大学)