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
Iterative Search Attribution for Deep Neural Networks
Zhiyu Zhu, Huaming Chen, Xinyi Wang, Jiayu Zhang, Zhibo Jin, Jason Xue, Jun Shen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Jacobian Regularizer-based Neural Granger Causality
Wanqi Zhou, Shuanghao Bai, Shujian Yu, Qibin Zhao, Badong Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization
Haocheng Xi, Yuxiang Chen, Kang Zhao, Kai Jun Teh, Jianfei Chen, Jun Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Joint Composite Latent Space Bayesian Optimization
Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat, Eytan Bakshy
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights $\textitIrreversibly$ and $\textitMonotonically$ Impairs “Difficult" Downstream Tasks in LLMs
Lu Yin, Ajay Kumar Jaiswal, Shiwei Liu, Souvik Kundu, Zhangyang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations
Stefan Sylvius Wagner, Stefan Harmeling
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
KISA: A Unified Keyframe Identifier and Skill Annotator for Long-Horizon Robotics Demonstrations
Longxin Kou, Fei Ni, Yan Zheng, Jinyi Liu, Yifu Yuan, Zibin Dong, Jianye Hao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache
Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, Xia Hu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation
Minsik Cho, Mohammad Rastegari, Devang Naik
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Kepler codebook
Junrong Lian, Ziyue Dong, Pengxu Wei, Wei Ke, Chang Liu, Qixiang Ye, Xiangyang Ji, Liang Lin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters
Brian M Cho, Yaroslav Mukhin, Kyra Gan, Ivana Malenica
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Kernel Semi-Implicit Variational Inference
Ziheng Cheng, Longlin Yu, Tianyu Xie, Shiyue Zhang, Cheng Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Kernel-Based Evaluation of Conditional Biological Sequence Models
Pierre Glaser, Steffanie Paul, Alissa M Hummer, Charlotte Deane, Debora Susan Marks, Alan Nawzad Amin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
KernelWarehouse: Rethinking the Design of Dynamic Convolution
Chao Li, Anbang Yao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs
Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou, Ye Yuan, Guoren Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning
Junnan Liu, Qianren Mao, Weifeng Jiang, Jianxin Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Knowledge Distillation with Auxiliary Variable
Bo Peng, Zhen Fang, Guangquan Zhang, Jie Lu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Knowledge Graphs Can be Learned with Just Intersection Features
Duy Le, Shaochen Zhong, Zirui Liu, Shuai Xu, Vipin Chaudhary, Kaixiong Zhou, Zhaozhuo Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models
Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri, Sachin Mehta, Mehrdad Farajtabar, Mohammad Rastegari, Oncel Tuzel
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Knowledge-aware Reinforced Language Models for Protein Directed Evolution
Yuhao Wang, Qiang Zhang, Ming Qin, Xiang Zhuang, Xiaotong Li, Zhichen Gong, Zeyuan Wang, Yu Zhao, Jianhua Yao, Keyan Ding, Huajun Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning
Hyungho Na, Il-Chul Moon
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LASER: Linear Compression in Wireless Distributed Optimization
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael Gastpar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LCA-on-the-Line: Benchmarking Out of Distribution Generalization with Class Taxonomies
Jia Shi, Gautam Rajendrakumar Gare, Jinjin Tian, Siqi Chai, Zhiqiu Lin, Arun Balajee Vasudevan, Di Feng, Francesco Ferroni, Shu Kong
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LESS: Selecting Influential Data for Targeted Instruction Tuning
Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, Sanjeev Arora, Danqi Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models
Tianci Liu, Haoyu Wang, Shiyang Wang, Yu Cheng, Jing Gao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning
Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo, Zhiqing Sun, Joshua B. Tenenbaum, Daniela Rus, Chuang Gan, Wojciech Matusik
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LLM-Empowered State Representation for Reinforcement Learning
Boyuan Wang, Yun Qu, Yuhang Jiang, Jianzhun Shao, Chang Liu, Wenming Yang, Xiangyang Ji
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LLaGA: Large Language and Graph Assistant
Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LLark: A Multimodal Instruction-Following Language Model for Music
Joshua P Gardner, Simon Durand, Daniel Stoller, Rachel M Bittner
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers
Anselm Paulus, Georg Martius, Vı́t Musil
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LQER: Low-Rank Quantization Error Reconstruction for LLMs
Cheng Zhang, Jianyi Cheng, George Anthony Constantinides, Yiren Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering
Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits
Chen-Chia Chang, Yikang Shen, Shaoze Fan, Jing Li, Shun Zhang, Ningyuan Cao, Yiran Chen, Xin Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LangCell: Language-Cell Pre-training for Cell Identity Understanding
Suyuan Zhao, Jiahuan Zhang, Yushuai Wu, Yizhen Luo, Zaiqing Nie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Langevin Policy for Safe Reinforcement Learning
Fenghao Lei, Long Yang, Shiting Wen, Zhixiong Huang, Zhiwang Zhang, Chaoyi Pang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models
Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
Zelai Xu, Chao Yu, Fei Fang, Yu Wang, Yi Wu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language Generation with Strictly Proper Scoring Rules
Chenze Shao, Fandong Meng, Yijin Liu, Jie Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language Models Represent Beliefs of Self and Others
Wentao Zhu, Zhining Zhang, Yizhou Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
Le Yu, Bowen Yu, Haiyang Yu, Fei Huang, Yongbin Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language Models as Science Tutors
Alexis Chevalier, Jiayi Geng, Alexander Wettig, Howard Chen, Sebastian Mizera, Toni Annala, Max Aragon, Arturo Rodriguez Fanlo, Simon Frieder, Simon Machado, Akshara Prabhakar, Ellie Thieu, Jiachen T. Wang, Zirui Wang, Xindi Wu, Mengzhou Xia, Wenhan Xia, Jiatong Yu, Junjie Zhu, Zhiyong Ren, Sanjeev Arora, Danqi Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language Models as Semantic Indexers
Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language Models with Conformal Factuality Guarantees
Christopher Mohri, Tatsunori Hashimoto
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition
Yicheng Liu, Jie Wen, Chengliang Liu, Xiaozhao Fang, Zuoyong Li, Yong Xu, Zheng Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin, George Konidaris, Nicolas Le Roux, Marc-Alexandre Côté, Xingdi Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
Sungwon Han, Jinsung Yoon, Sercan O Arik, Tomas Pfister
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Large Language Models are Geographically Biased
Rohin Manvi, Samar Khanna, Marshall Burke, David B. Lobell, Stefano Ermon
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Large Scale Dataset Distillation with Domain Shift
Noel Loo, Alaa Maalouf, Ramin Hasani, Mathias Lechner, Alexander Amini, Daniela Rus
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Larimar: Large Language Models with Episodic Memory Control
Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarathkrishna Swaminathan, Sihui Dai, Aurelie Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jiri Navratil, Soham Dan, Pin-Yu Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Latent Logic Tree Extraction for Event Sequence Explanation from LLMs
Zitao Song, Chao Yang, Chaojie Wang, Bo An, Shuang Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping
Ben Lonnqvist, Zhengqing Wu, Michael Herzog
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
Xinlei Niu, Christian Walder, Jing Zhang, Charles Patrick Martin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Latent Space Symmetry Discovery
Jianke Yang, Nima Dehmamy, Robin Walters, Rose Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Latent variable model for high-dimensional point process with structured missingness
Maksim Sinelnikov, Manuel Haussmann, Harri Lähdesmäki
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency
Runqi Lin, Chaojian Yu, Bo Han, Hang Su, Tongliang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging
Jinuk Kim, Marwa El Halabi, Mingi Ji, Hyun Oh Song
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Layerwise Change of Knowledge in Neural Networks
Xu Cheng, Lei Cheng, Zhaoran Peng, Yang Xu, Tian Han, Quanshi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning
Jinsoo Yoo, Yunpeng Liu, Frank Wood, Geoff Pleiss
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LeaPformer: Enabling Linear Transformers for Autoregressive and Simultaneous Tasks via Learned Proportions
Victor Agostinelli Iii, Sanghyun Hong, Lizhong Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning 1-Bit Tiny Object Detector with Discriminative Feature Refinement
Sheng Xu, Mingze Wang, Yanjing Li, Mingbao Lin, Baochang Zhang, David Doermann, Xiao Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking
Yongxin Li, Mengyuan Liu, You Wu, Xucheng Wang, Xiangyang Yang, Shuiwang Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Associative Memories with Gradient Descent
Vivien Cabannes, Berfin Simsek, Alberto Bietti
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
Yuke Li, Guangyi Chen, Ben Abramowitz, Stefano Anzellotti, Donglai Wei
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Causal Dynamics Models in Object-Oriented Environments
Zhongwei Yu, Jingqing Ruan, Dengpeng Xing
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Causal Relations from Subsampled Time Series with Two Time-Slices
Anpeng Wu, Haoxuan Li, Kun Kuang, Zhang Keli, Fei Wu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments
Antoine Dedieu, Wolfgang Lehrach, Guangyao Zhou, Dileep George, Miguel Lazaro-Gredilla
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation
Guorui Quan, Zhiqiang Xu, Guiliang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
Arvi Jonnarth, Jie Zhao, Michael Felsberg
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Decision Policies with Instrumental Variables through Double Machine Learning
Daqian Shao, Ashkan Soleymani, Francesco Quinzan, Marta Kwiatkowska
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Decision Trees and Forests with Algorithmic Recourse
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
Machine Learning
日本大学: 東京科学大学 / 九州大学
2024 · ICML
Learning Divergence Fields for Shift-Robust Graph Representations
Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence
Sascha Xu, Nils Philipp Walter, Janis Kalofolias, Jilles Vreeken
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Graph Representation via Graph Entropy Maximization
Ziheng Sun, Xudong Wang, Chris Ding, Jicong Fan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding
Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, Siddharth N, Shuo Chen, Mahesh K. Marina
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning High-Order Relationships of Brain Regions
Weikang Qiu, Huangrui Chu, Selena Wang, Haolan Zuo, Xiaoxiao Li, Yize Zhao, Rex Ying
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Iterative Reasoning through Energy Diffusion
Yilun Du, Jiayuan Mao, Joshua B. Tenenbaum
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition
Tong Wei, Zhen Mao, Zi-Hao Zhou, Yuanyu Wan, Min-Ling Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Latent Dynamic Robust Representations for World Models
Ruixiang Sun, Hongyu Zang, Xin Li, Riashat Islam
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Latent Space Hierarchical EBM Diffusion Models
Jiali Cui, Tian Han
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders
Xue Yu, Muchen Li, Yan Leng, Renjie Liao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Linear Block Error Correction Codes
Yoni Choukroun, Lior Wolf
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds
Yuyang Zhang, Shahriar Talebi, Na Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Mixtures of Gaussian Processes through Random Projection
Emmanuel Akeweje, Mimi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Modality Knowledge Alignment for Cross-Modality Transfer
Wenxuan Ma, Shuang Li, Lincan Cai, Jingxuan Kang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Multiple Secrets in Mastermind
Milind Prabhu, David Woodruff
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Optimal Deterministic Policies with Stochastic Policy Gradients
Alessandro Montenegro, Marco Mussi, Alberto Maria Metelli, Matteo Papini
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series
Asterios Tsiourvas, Wei Sun, Georgia Perakis, Pin-Yu Chen, Yada Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Pseudo-Contractive Denoisers for Inverse Problems
Deliang Wei, Peng Chen, Fang Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Reward for Robot Skills Using Large Language Models via Self-Alignment
Yuwei Zeng, Yao Mu, Lin Shao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Scale-Aware Spatio-temporal Implicit Representation for Event-based Motion Deblurring
Wei Yu, Jianing Li, Shengping Zhang, Xiangyang Ji
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
Baohong Li, Haoxuan Li, Ruoxuan Xiong, Anpeng Wu, Fei Wu, Kun Kuang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment Problem
Zhentao Tan, Yadong Mu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
Minh Hoang, Azza Fadhel, Aryan Deshwal, Jana Doppa, Trong Nghia Hoang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
Vivek Myers, Chongyi Zheng, Anca Dragan, Sergey Levine, Benjamin Eysenbach
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Universal Predictors
Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Gregoire Deletang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning Useful Representations of Recurrent Neural Network Weight Matrices
Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber
Machine Learning
日本大学: 関与なし（対象大学）