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
Learning a Diffusion Model Policy from Rewards via Q-Score Matching
Michael Psenka, Alejandro Escontrela, Pieter Abbeel, Yi Ma
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning and Forgetting Unsafe Examples in Large Language Models
Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning from Integral Losses in Physics Informed Neural Networks
Ehsan Saleh, Saba Ghaffari, Tim Bretl, Luke Olson, Matthew West
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features
Thalles Silva, Helio Pedrini, Adı́n Ramı́rez Rivera
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning from Streaming Data when Users Choose
Jinyan Su, Sarah Dean
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs
Jordan Dotzel, Yuzong Chen, Bahaa Kotb, Sushma Prasad, Gang Wu, Sheng Li, Mohamed S Abdelfattah, Zhiru Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning in Deep Factor Graphs with Gaussian Belief Propagation
Seth Nabarro, Mark Van Der Wilk, Andrew Davison
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method
Qinghua Tao, Francesco Tonin, Alex Lambert, Yingyi Chen, Panagiotis Patrinos, Johan Suykens
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning the Target Network in Function Space
Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis
Yingying Li, Jing Yu, Lauren Conger, Taylan Kargin, Adam Wierman
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Compile Programs to Neural Networks
Logan Weber, Jesse Michel, Alex Renda, Michael Carbin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Continually Learn with the Bayesian Principle
Soochan Lee, Hyeonseong Jeon, Jaehyeon Son, Gunhee Kim
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Explore for Stochastic Gradient MCMC
Seunghyun Kim, Seohyeon Jung, Seonghyeon Kim, Juho Lee
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Explore in POMDPs with Informational Rewards
Annie Xie, Logan Mondal Bhamidipaty, Evan Zheran Liu, Joey Hong, Sergey Levine, Chelsea Finn
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Infer Generative Template Programs for Visual Concepts
R. Kenny Jones, Siddhartha Chaudhuri, Daniel Ritchie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Intervene on Concept Bottlenecks
David Steinmann, Wolfgang Stammer, Felix Friedrich, Kristian Kersting
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Model the World With Language
Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca Dragan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Play Atari in a World of Tokens
Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning
Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V Chawla, Stan Z. Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Reach Goals via Diffusion
Vineet Jain, Siamak Ravanbakhsh
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Remove Cuts in Integer Linear Programming
Pol Puigdemont, Stratis Skoulakis, Grigorios Chrysos, Volkan Cevher
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Route Among Specialized Experts for Zero-Shot Generalization
Mohammed Muqeeth, Haokun Liu, Yufan Liu, Colin Raffel
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Scale Logits for Temperature-Conditional GFlowNets
Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woo Chang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
Brahma S Pavse, Matthew Zurek, Yudong Chen, Qiaomin Xie, Josiah P. Hanna
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning with 3D rotations, a hitchhiker’s guide to SO(3)
Andreas René Geist, Jonas Frey, Mikel Zhobro, Anna Levina, Georg Martius
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning with Adaptive Resource Allocation
Jing Wang, Miao Yu, Peng Zhao, Zhi-Hua Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical
Wei Wang, Takashi Ishida, Yu-Jie Zhang, Gang Niu, Masashi Sugiyama
Machine Learning
日本大学: 東京大学
2024 · ICML
Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency
Yangfan Liu, Jiaqi Lv, Xin Geng, Ning Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation
Yuanhao Pu, Xiaolong Chen, Xu Huang, Jin Chen, Defu Lian, Enhong Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
Daniel Dodd, Louis Sharrock, Christopher Nemeth
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Less is More: on the Over-Globalizing Problem in Graph Transformers
Yujie Xing, Xiao Wang, Yibo Li, Hai Huang, Chuan Shi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!
Milad Sefidgaran, Romain Chor, Abdellatif Zaidi, Yijun Wan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Let Go of Your Labels with Unsupervised Transfer
Artyom Gadetsky, Yulun Jiang, Maria Brbic
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification
Jay Gala, Pengtao Xie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Leveraging (Biased) Information: Multi-armed Bandits with Offline Data
Wang Chi Cheung, Lixing Lyu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Leveraging Attractor Dynamics in Spatial Navigation for Better Language Parsing
Xiaolong Zou, Xingxing Cao, Xiaojiao Yang, Bo Hong
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference
Marvin Schmitt, Desi R. Ivanova, Daniel Habermann, Ullrich Koethe, Paul-Christian Bürkner, Stefan T. Radev
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Leveraging VLM-Based Pipelines to Annotate 3D Objects
Rishabh Kabra, Loic Matthey, Alexander Lerchner, Niloy Mitra
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Libra: Building Decoupled Vision System on Large Language Models
Yifan Xu, Xiaoshan Yang, Yaguang Song, Changsheng Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras
Tzu-Yuan Lin, Minghan Zhu, Maani Ghaffari
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Light and Optimal Schrödinger Bridge Matching
Nikita Gushchin, Sergei Kholkin, Evgeny Burnaev, Alexander Korotin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Lightweight Image Super-Resolution via Flexible Meta Pruning
Yulun Zhang, Kai Zhang, Luc Van Gool, Martin Danelljan, Fisher Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Limited Preference Aided Imitation Learning from Imperfect Demonstrations
Xingchen Cao, Fan-Ming Luo, Junyin Ye, Tian Xu, Zhilong Zhang, Yang Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback
Songyang Gao, Qiming Ge, Wei Shen, Shihan Dou, Junjie Ye, Xiao Wang, Rui Zheng, Yicheng Zou, Zhi Chen, Hang Yan, Qi Zhang, Dahua Lin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Linear Explanations for Individual Neurons
Tuomas Oikarinen, Tsui-Wei Weng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Linguistic Calibration of Long-Form Generations
Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Liouville Flow Importance Sampler
Yifeng Tian, Nishant Panda, Yen Ting Lin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Listenable Maps for Audio Classifiers
Francesco Paissan, Mirco Ravanelli, Cem Subakan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Listening to the noise: Blind Denoising with Gibbs Diffusion
David Heurtel-Depeiges, Charles Margossian, Ruben Ohana, Bruno Régaldo-Saint Blancard
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Listwise Reward Estimation for Offline Preference-based Reinforcement Learning
Heewoong Choi, Sangwon Jung, Hongjoon Ahn, Taesup Moon
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LoCoCo: Dropping In Convolutions for Long Context Compression
Ruisi Cai, Yuandong Tian, Zhangyang Wang, Beidi Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LoRA Training in the NTK Regime has No Spurious Local Minima
Uijeong Jang, Jason D. Lee, Ernest K. Ryu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LoRA+: Efficient Low Rank Adaptation of Large Models
Soufiane Hayou, Nikhil Ghosh, Bin Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models
Guangyan Li, Yongqiang Tang, Wensheng Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Local Causal Structure Learning in the Presence of Latent Variables
Feng Xie, Zheng Li, Peng Wu, Yan Zeng, Chunchen Liu, Zhi Geng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions
Harrie Oosterhuis, Lijun Lyu, Avishek Anand
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Local vs. Global Interpretability: A Computational Complexity Perspective
Shahaf Bassan, Guy Amir, Guy Katz
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics
Siqi Miao, Zhiyuan Lu, Mia Liu, Javier Duarte, Pan Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Localizing Task Information for Improved Model Merging and Compression
Ke Wang, Nikolaos Dimitriadis, Guillermo Ortiz-Jimenez, François Fleuret, Pascal Frossard
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy
Ziqin Chen, Yongqiang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization
Ziqing Fan, Shengchao Hu, Jiangchao Yao, Gang Niu, Ya Zhang, Masashi Sugiyama, Yanfeng Wang
Machine Learning
日本大学: 東京大学
2024 · ICML
Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies
Alex Deweese, Guannan Qu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Log Neural Controlled Differential Equations: The Lie Brackets Make A Difference
Benjamin Walker, Andrew Donald Mcleod, Tiexin Qin, Yichuan Cheng, Haoliang Li, Terry Lyons
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Logistic Variational Bayes Revisited
Michael Komodromos, Marina Evangelou, Sarah Lucie Filippi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning
Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Long Range Propagation on Continuous-Time Dynamic Graphs
Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio, Davide Bacciu, Claas Grohnfeldt
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
Jiang-Xin Shi, Tong Wei, Zhi Zhou, Jie-Jing Shao, Xin-Yan Han, Yu-Feng Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu, Ning Shang, Jiahang Xu, Fan Yang, Mao Yang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
Toru Shirakawa, Yi Li, Yulun Wu, Sky Qiu, Yuxuan Li, Mingduo Zhao, Hiroyasu Iso, Mark J. Van Der Laan
Machine Learning
日本大学: 大阪医科薬科大学 / 大阪大学
2024 · ICML
Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining
Qi Zhang, Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Lookbehind-SAM: k steps back, 1 step forward
Goncalo Mordido, Pranshu Malviya, Aristide Baratin, Sarath Chandar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Loss Shaping Constraints for Long-Term Time Series Forecasting
Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Low-Cost High-Power Membership Inference Attacks
Sajjad Zarifzadeh, Philippe Liu, Reza Shokri
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery
Yassir Jedra, William Réveillard, Stefan Stojanovic, Alexandre Proutiere
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Low-Rank Similarity Mining for Multimodal Dataset Distillation
Yue Xu, Zhilin Lin, Yusong Qiu, Cewu Lu, Yong-Lu Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation
Lujie Yang, Hongkai Dai, Zhouxing Shi, Cho-Jui Hsieh, Russ Tedrake, Huan Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent
Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
Justin Chen, Swarnadeep Saha, Elias Stengel-Eskin, Mohit Bansal
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation
Alexandre Hayderi, Amin Saberi, Ellen Vitercik, Anders Wikum
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
Jiarong Pan, Stefan Falkner, Felix Berkenkamp, Joaquin Vanschoren
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations
Zhangyu Wang, Gengchen Mai, Krzysztof Janowicz, Ni Lao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MD tree: a model-diagnostic tree grown on loss landscape
Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MEMORYLLM: Towards Self-Updatable Large Language Models
Yu Wang, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li, Jingfeng Yang, Qingyu Yin, Zheng Li, Xian Li, Bing Yin, Jingbo Shang, Julian Mcauley
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series
Jufang Duan, Wei Zheng, Yangzhou Du, Wenfa Wu, Haipeng Jiang, Hongsheng Qi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MFTN: A Multi-scale Feature Transfer Network Based on IMatchFormer for Hyperspectral Image Super-Resolution
Shuying Huang, Mingyang Ren, Yong Yang, Xiaozheng Wang, Yingzhi Wei
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MGit: A Model Versioning and Management System
Wei Hao, Daniel Mendoza, Rafael Mendes, Deepak Narayanan, Amar Phanishayee, Asaf Cidon, Junfeng Yang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis
Luyuan Xie, Manqing Lin, Tianyu Luan, Cong Li, Yuejian Fang, Qingni Shen, Zhonghai Wu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness
Yahong Zhang, Chenchen Fan, Donghui Chen, Congrui Li, Wenli Ouyang, Mingda Zhu, Junchi Yan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
Qian Huang, Jian Vora, Percy Liang, Jure Leskovec
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation
Bowen Tao, Xin-Chun Li, De-Chuan Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization
Yu Zhang, Qi Zhang, Zixuan Gong, Yiwei Shi, Yepeng Liu, Duoqian Miao, Yang Liu, Ke Liu, Kun Yi, Wei Fan, Liang Hu, Changwei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark
Dongping Chen, Ruoxi Chen, Shilin Zhang, Yaochen Wang, Yinuo Liu, Huichi Zhou, Qihui Zhang, Yao Wan, Pan Zhou, Lichao Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities
Weihao Yu, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu, Xinchao Wang, Lijuan Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MMPareto: Boosting Multimodal Learning with Innocent Unimodal Assistance
Yake Wei, Di Hu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
Kaining Ying, Fanqing Meng, Jin Wang, Zhiqian Li, Han Lin, Yue Yang, Hao Zhang, Wenbo Zhang, Yuqi Lin, Shuo Liu, Jiayi Lei, Quanfeng Lu, Runjian Chen, Peng Xu, Renrui Zhang, Haozhe Zhang, Peng Gao, Yali Wang, Yu Qiao, Ping Luo, Kaipeng Zhang, Wenqi Shao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence
Hongduan Tian, Feng Liu, Tongliang Liu, Bo Du, Yiu-Ming Cheung, Bo Han
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MOMENT: A Family of Open Time-series Foundation Models
Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li, Artur Dubrawski
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data
Jian Wang, Xin Lan, Yuxin Tian, Jiancheng Lv
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MS-TIP: Imputation Aware Pedestrian Trajectory Prediction
Pranav Singh Chib, Achintya Nath, Paritosh Kabra, Ishu Gupta, Pravendra Singh
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
Jianan Zhou, Zhiguang Cao, Yaoxin Wu, Wen Song, Yining Ma, Jie Zhang, Xu Chi
Machine Learning
日本大学: 関与なし（対象大学）