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

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
Effective Federated Graph Matching
Yang Zhou, Zijie Zhang, Zeru Zhang, Lingjuan Lyu, Wei-Shinn Ku
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing
Youwei Shu, Xi Xiao, Derui Wang, Yuxin Cao, Siji Chen, Jason Xue, Linyi Li, Bo Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
Yizhe Huang, Anji Liu, Fanqi Kong, Yaodong Yang, Song-Chun Zhu, Xue Feng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond
Dingzhi Yu, Yunuo Cai, Wei Jiang, Lijun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Algorithms for Sum-Of-Minimum Optimization
Lisang Ding, Ziang Chen, Xinshang Wang, Wotao Yin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
Shuyu Cheng, Yibo Miao, Yinpeng Dong, Xiao Yang, Xiao-Shan Gao, Jun Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Contextual Bandits with Uninformed Feedback Graphs
Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs
Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C. Aggarwal, Suhang Wang, Vasant G Honavar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Denoising Diffusion via Probabilistic Masking
Weizhong Zhang, Zhiwei Zhang, Renjie Pi, Zhongming Jin, Yuan Gao, Jieping Ye, Kani Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Error Certification for Physics-Informed Neural Networks
Francisco Eiras, Adel Bibi, Rudy R Bunel, Krishnamurthy Dj Dvijotham, Philip Torr, M. Pawan Kumar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Exploration for LLMs
Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling
Danil Provodin, Maurits Clemens Kaptein, Mykola Pechenizkiy
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Mixture Learning in Black-Box Variational Inference
Alexandra Hotti, Oskar Kviman, Ricky Molén, Vı́ctor Elvira, Jens Lagergren
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation
Yu-Yang Qian, Peng Zhao, Yu-Jie Zhang, Masashi Sugiyama, Zhi-Hua Zhou
Machine Learning
日本大学: 東京大学
2024 · ICML
Efficient Online Set-valued Classification with Bandit Feedback
Zhou Wang, Xingye Qiao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient PAC Learnability of Dynamical Systems Over Multilayer Networks
Zirou Qiu, Abhijin Adiga, Madhav Marathe, S. S. Ravi, Daniel Rosenkrantz, Richard Stearns, Anil Kumar Vullikanti
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Pareto Manifold Learning with Low-Rank Structure
Weiyu Chen, James Kwok
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design
Shuze Liu, Shangtong Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling
Yuanbang Liang, Jing Wu, Yu-Kun Lai, Yipeng Qin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Stochastic Approximation of Minimax Excess Risk Optimization
Lijun Zhang, Haomin Bai, Wei-Wei Tu, Ping Yang, Yao Hu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient Value Iteration for s-rectangular Robust Markov Decision Processes
Navdeep Kumar, Kaixin Wang, Kfir Yehuda Levy, Shie Mannor
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient World Models with Context-Aware Tokenization
Vincent Micheli, Eloi Alonso, François Fleuret
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
Changze Lv, Yansen Wang, Dongqi Han, Xiaoqing Zheng, Xuanjing Huang, Dongsheng Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
Shengjie Wang, Shaohuai Liu, Weirui Ye, Jiacheng You, Yang Gao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
Shengyao Lu, Bang Liu, Keith G Mills, Jiao He, Di Niu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Eluder-based Regret for Stochastic Contextual MDPs
Orin Levy, Asaf Cassel, Alon Cohen, Yishay Mansour
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Embarrassingly Parallel GFlowNets
Tiago Silva, Luiz Max Carvalho, Amauri H Souza, Samuel Kaski, Diego Mesquita
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Embodied CoT Distillation From LLM To Off-the-shelf Agents
Wonje Choi, Woo Kyung Kim, Minjong Yoo, Honguk Woo
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Emergence of In-Context Reinforcement Learning from Noise Distillation
Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Emergent Equivariance in Deep Ensembles
Jan E Gerken, Pan Kessel
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Emergent Representations of Program Semantics in Language Models Trained on Programs
Charles Jin, Martin Rinard
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Empowering Graph Invariance Learning with Deep Spurious Infomax
Tianjun Yao, Yongqiang Chen, Zhenhao Chen, Kai Hu, Zhiqiang Shen, Kun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enabling Few-Shot Learning with PID Control: A Layer Adaptive Optimizer
Le Yu, Xinde Li, Pengfei Zhang, Zhentong Zhang, Fir Dunkin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enabling Uncertainty Estimation in Iterative Neural Networks
Nikita Durasov, Doruk Oner, Jonathan Donier, Hieu Le, Pascal Fua
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Encodings for Prediction-based Neural Architecture Search
Yash Akhauri, Mohamed S Abdelfattah
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
Lirui Luo, Guoxi Zhang, Hongming Xu, Yaodong Yang, Cong Fang, Qing Li
Machine Learning
日本大学: 京都大学
2024 · ICML
Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic
Nicolas Alder, Ralf Herbrich
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
Xu-Hui Liu, Tian-Shuo Liu, Shengyi Jiang, Ruifeng Chen, Zhilong Zhang, Xinwei Chen, Yang Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Energy-based Backdoor Defense without Task-Specific Samples and Model Retraining
Yudong Gao, Honglong Chen, Peng Sun, Zhe Li, Junjian Li, Huajie Shao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enforcing Constraints in RNA Secondary Structure Predictions: A Post-Processing Framework Based on the Assignment Problem
Geewon Suh, Gyeongjo Hwang, Seokjun Kang, Doojin Baek, Mingeun Kang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Yujia Liu, Tong Bu, Jianhao Ding, Zecheng Hao, Tiejun Huang, Zhaofei Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation
Lan Li, Xin-Chun Li, Han-Jia Ye, De-Chuan Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Cross-Modal Fine-Tuning with Gradually Intermediate Modality Generation
Lincan Cai, Shuang Li, Wenxuan Ma, Jingxuan Kang, Binhui Xie, Zixun Sun, Chengwei Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Implicit Shape Generators Using Topological Regularizations
Liyan Chen, Yan Zheng, Yang Li, Lohit Anirudh Jagarapu, Haoxiang Li, Hao Kang, Gang Hua, Qixing Huang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
Zheng Huang, Qihui Yang, Dawei Zhou, Yujun Yan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models
Zixin Zhang, Fan Qi, Changsheng Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Sufficient Dimension Reduction via Hellinger Correlation
Seungbeom Hong, Ilmun Kim, Jun Song
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
Pranav Singh Chib, Pravendra Singh
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning
Yun-Hsuan Lien, Ping-Chun Hsieh, Tzu-Mao Li, Yu-Shuen Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Enhancing Vision Transformer: Amplifying Non-Linearity in Feedforward Network Module
Yixing Xu, Chao Li, Dong Li, Xiao Sheng, Fan Jiang, Lu Tian, Ashish Sirasao, Emad Barsoum
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Ensemble Pruning for Out-of-distribution Generalization
Fengchun Qiao, Xi Peng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Entropy-Reinforced Planning with Large Language Models for Drug Discovery
Xuefeng Liu, Chih-Chan Tien, Peng Ding, Songhao Jiang, Rick L. Stevens
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Environment Design for Inverse Reinforcement Learning
Thomas Kleine Buening, Victor Villin, Christos Dimitrakakis
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning
Jongsuk Kim, Hyeongkeun Lee, Kyeongha Rho, Junmo Kim, Joon Son Chung
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction
Yang Zhang, Zhewei Wei, Ye Yuan, Chongxuan Li, Wenbing Huang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Equilibrium of Data Markets with Externality
Safwan Hossain, Yiling Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Equivariant Deep Weight Space Alignment
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Equivariant Diffusion for Crystal Structure Prediction
Peijia Lin, Pin Chen, Rui Jiao, Qing Mo, Cen Jianhuan, Wenbing Huang, Yang Liu, Dan Huang, Yutong Lu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Equivariant Frames and the Impossibility of Continuous Canonicalization
Nadav Dym, Hannah Lawrence, Jonathan W. Siegel
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Equivariant Graph Neural Operator for Modeling 3D Dynamics
Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
Kai Gan, Tong Wei
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Error Feedback Can Accurately Compress Preconditioners
Ionut-Vlad Modoranu, Aleksei Kalinov, Eldar Kurtic, Elias Frantar, Dan Alistarh
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Estimating Barycenters of Distributions with Neural Optimal Transport
Alexander Kolesov, Petr Mokrov, Igor Udovichenko, Milena Gazdieva, Gudmund Pammer, Evgeny Burnaev, Alexander Korotin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Estimating Canopy Height at Scale
Jan Pauls, Max Zimmer, Una M. Kelly, Martin Schwartz, Sassan Saatchi, Philippe Ciais, Sebastian Pokutta, Martin Brandt, Fabian Gieseke
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
Undral Byambadalai, Tatsushi Oka, Shota Yasui
Machine Learning
日本大学: 慶應義塾大学
2024 · ICML
Estimating Unknown Population Sizes Using the Hypergeometric Distribution
Liam Hodgson, Danilo Bzdok
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Estimating the Permanent by Nesting Importance Sampling
Juha Harviainen, Mikko Koivisto
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples
Andrew Craig Cullen, Shijie Liu, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems
David T Hoffmann, Simon Schrodi, Jelena Bratulić, Nadine Behrmann, Volker Fischer, Thomas Brox
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting
Jiaxu Wang, Junhao He, Ziyi Zhang, Mingyuan Sun, Jingkai Sun, Renjing Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EvIL: Evolution Strategies for Generalisable Imitation Learning
Silvia Sapora, Gokul Swamy, Chris Lu, Yee Whye Teh, Jakob Nicolaus Foerster
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
Dachun Kai, Jiayao Lu, Yueyi Zhang, Xiaoyan Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evaluating Model Bias Requires Characterizing its Mistakes
Isabela Albuquerque, Jessica Schrouff, David Warde-Farley, Ali Taylan Cemgil, Sven Gowal, Olivia Wiles
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evaluating Quantized Large Language Models
Shiyao Li, Xuefei Ning, Luning Wang, Tengxuan Liu, Xiangsheng Shi, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models
Mingrui Wu, Jiayi Ji, Oucheng Huang, Jiale Li, Yuhang Wu, Xiaoshuai Sun, Rongrong Ji
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks
Linyuan Gong, Sida Wang, Mostafa Elhoushi, Alvin Cheung
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evaluation of Test-Time Adaptation Under Computational Time Constraints
Motasem Alfarra, Hani Itani, Alejandro Pardo, Shyma Yaser Alhuwaider, Merey Ramazanova, Juan Camilo Perez, Zhipeng Cai, Matthias Müller, Bernard Ghanem
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evaluation of Trajectory Distribution Predictions with Energy Score
Novin Shahroudi, Mihkel Lepson, Meelis Kull
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search
Pengyi Li, Yan Zheng, Hongyao Tang, Xian Fu, Jianye Hao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun, Kevin Choi, Balaji Veeramani, Alison Hu, Edward Bowen, Tyler Cody, Dawei Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model
Fei Liu, Tong Xialiang, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evolution-Inspired Loss Functions for Protein Representation Learning
Chengyue Gong, Adam Klivans, James Madigan Loy, Tianlong Chen, Qiang Liu, Daniel Jesus Diaz
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Evolving Subnetwork Training for Large Language Models
Hanqi Li, Lu Chen, Da Ma, Zijian Wu, Su Zhu, Kai Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking
Wenshuo Li, Xinghao Chen, Han Shu, Yehui Tang, Yunhe Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers
Brian K Chen, Tianyang Hu, Hui Jin, Hwee Kuan Lee, Kenji Kawaguchi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Exact Soft Analytical Side-Channel Attacks using Tractable Circuits
Thomas Wedenig, Rishub Nagpal, Gaëtan Cassiers, Stefan Mangard, Robert Peharz
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Executable Code Actions Elicit Better LLM Agents
Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li, Hao Peng, Heng Ji
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Expand-and-Cluster: Parameter Recovery of Neural Networks
Flavio Martinelli, Berfin Simsek, Wulfram Gerstner, Johanni Brea
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning
Chia-Cheng Chiang, Li-Cheng Lan, Wei-Fang Sun, Chien Feng, Cho-Jui Hsieh, Chun-Yi Lee
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Experts Don’t Cheat: Learning What You Don’t Know By Predicting Pairs
Daniel D. Johnson, Daniel Tarlow, David Duvenaud, Chris J. Maddison
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Explain Temporal Black-Box Models via Functional Decomposition
Linxiao Yang, Yunze Tong, Xinyue Gu, Liang Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Explaining Graph Neural Networks via Structure-aware Interaction Index
Ngoc Bui, Hieu Trung Nguyen, Viet Anh Nguyen, Rex Ying
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Explaining Probabilistic Models with Distributional Values
Luca Franceschi, Michele Donini, Cedric Archambeau, Matthias Seeger
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Exploiting Code Symmetries for Learning Program Semantics
Kexin Pei, Weichen Li, Qirui Jin, Shuyang Liu, Scott Geng, Lorenzo Cavallaro, Junfeng Yang, Suman Jana
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Exploiting Human-AI Dependence for Learning to Defer
Zixi Wei, Yuzhou Cao, Lei Feng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Exploiting Negative Samples: A Catalyst for Cohort Discovery in Healthcare Analytics
Kaiping Zheng, Horng-Ruey Chua, Melanie Herschel, H. V. Jagadish, Beng Chin Ooi, James Wei Luen Yip
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Exploration and Anti-Exploration with Distributional Random Network Distillation
Kai Yang, Jian Tao, Jiafei Lyu, Xiu Li
Machine Learning
日本大学: 関与なし（対象大学）