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
StyDeSty: Min-Max Stylization and Destylization for Single Domain Generalization
Songhua Liu, Xin Jin, Xingyi Yang, Jingwen Ye, Xinchao Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SuDA: Support-based Domain Adaptation for Sim2Real Hinge Joint Tracking with Flexible Sensors
Fang Jiawei, Haishan Song, Chengxu Zuo, Xiaoxia Gao, Xiaowei Chen, Shihui Guo, Yipeng Qin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sub-token ViT Embedding via Stochastic Resonance Transformers
Dong Lao, Yangchao Wu, Tian Yu Liu, Alex Wong, Stefano Soatto
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments
Runfa Chen, Ling Wang, Yu Du, Tianrui Xue, Fuchun Sun, Jianwei Zhang, Wenbing Huang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Subgoal-based Demonstration Learning for Formal Theorem Proving
Xueliang Zhao, Wenda Li, Lingpeng Kong
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
Guy Bar-Shalom, Beatrice Bevilacqua, Haggai Maron
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Subhomogeneous Deep Equilibrium Models
Pietro Sittoni, Francesco Tudisco
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Submodular framework for structured-sparse optimal transport
Piyushi Manupriya, Pratik Jawanpuria, Karthik S. Gurumoorthy, Sakethanath Jagarlapudi, Bamdev Mishra
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
Ossi Räisä, Joonas Jälkö, Antti Honkela
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Successor Features for Efficient Multi-Subject Controlled Text Generation
Meng Cao, Mehdi Fatemi, Jackie Ck Cheung, Samira Shabanian
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Superpoint Gaussian Splatting for Real-Time High-Fidelity Dynamic Scene Reconstruction
Diwen Wan, Ruijie Lu, Gang Zeng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation
Thomas Merth, Qichen Fu, Mohammad Rastegari, Mahyar Najibi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Supervised Matrix Factorization: Local Landscape Analysis and Applications
Joowon Lee, Hanbaek Lyu, Weixin Yao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SurfPro: Functional Protein Design Based on Continuous Surface
Zhenqiao Song, Tinglin Huang, Lei Li, Wengong Jin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Surface-VQMAE: Vector-quantized Masked Auto-encoders on Molecular Surfaces
Fang Wu, Stan Z. Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Surprisingly Strong Performance Prediction with Neural Graph Features
Gabriela Kadlecová, Jovita Lukasik, Martin Pilát, Petra Vidnerová, Mahmoud Safari, Roman Neruda, Frank Hutter
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation
Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Switchable Decision: Dynamic Neural Generation Networks
Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Switched Flow Matching: Eliminating Singularities via Switching ODEs
Qunxi Zhu, Wei Lin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Switching the Loss Reduces the Cost in Batch Reinforcement Learning
Alex Ayoub, Kaiwen Wang, Vincent Liu, Samuel Robertson, James Mcinerney, Dawen Liang, Nathan Kallus, Csaba Szepesvari
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment
Ziping Ma, Furong Xu, Jian Liu, Ming Yang, Qingpei Guo
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion
Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli Shama Sastry, Siddharth Gururani, Sageev Oore, Yisong Yue
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Symmetric Matrix Completion with ReLU Sampling
Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
Hyeonah Kim, Minsu Kim, Sungsoo Ahn, Jinkyoo Park
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Symmetry Induces Structure and Constraint of Learning
Liu Ziyin
Machine Learning
日本大学: 東京大学
2024 · ICML
Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs
Mingyu Kim, Kim Jun-Seong, Se-Young Yun, Jin-Hwa Kim
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision
Zhuo Chen, Jacob Mccarran, Esteban Vizcaino, Marin Soljacic, Di Luo
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
Yichuan Mo, Hui Huang, Mingjie Li, Ang Li, Yisen Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TIC-TAC: A Framework For Improved Covariance Estimation In Deep Heteroscedastic Regression
Megh Shukla, Mathieu Salzmann, Alexandre Alahi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TSLANet: Rethinking Transformers for Time Series Representation Learning
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Xiaoli Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TVE: Learning Meta-attribution for Transferable Vision Explainer
Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules
Weijieying Ren, Xiaoting Li, Huiyuan Chen, Vineeth Rakesh, Zhuoyi Wang, Mahashweta Das, Vasant G Honavar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images
Jun-Peng Jiang, Han-Jia Ye, Leye Wang, Yang Yang, Yuan Jiang, De-Chuan Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
Wanpeng Zhang, Yilin Li, Boyu Yang, Zongqing Lu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn, Kijung Shin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicolo Fusi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tandem Transformers for Inference Efficient LLMs
Aishwarya P S, Pranav Ajit Nair, Yashas Samaga B L, Toby James Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation
Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A Ramirez, Christopher K Harris, A. Rupam Mahmood, Dale Schuurmans
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Task Groupings Regularization: Data-Free Meta-Learning with Heterogeneous Pre-trained Models
Yongxian Wei, Zixuan Hu, Li Shen, Zhenyi Wang, Yu Li, Chun Yuan, Dacheng Tao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning
Yusong Hu, De Cheng, Dingwen Zhang, Nannan Wang, Tongliang Liu, Xinbo Gao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Taylor Videos for Action Recognition
Lei Wang, Xiuyuan Yuan, Tom Gedeon, Liang Zheng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tell, Don’t Show: Language Guidance Eases Transfer Across Domains in Images and Videos
Tarun Kalluri, Bodhisattwa Prasad Majumder, Manmohan Chandraker
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
Zijian Guo, Weichao Zhou, Wenchao Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning
Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Test-Time Degradation Adaptation for Open-Set Image Restoration
Yuanbiao Gou, Haiyu Zhao, Boyun Li, Xinyan Xiao, Xi Peng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Test-Time Model Adaptation with Only Forward Passes
Shuaicheng Niu, Chunyan Miao, Guohao Chen, Pengcheng Wu, Peilin Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Test-Time Regret Minimization in Meta Reinforcement Learning
Mirco Mutti, Aviv Tamar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Testing the Feasibility of Linear Programs with Bandit Feedback
Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama, Clayton Scott
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Balanced-Pairwise-Affinities Feature Transform
Daniel Shalam, Simon Korman
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents
Yatin Dandi, Emanuele Troiani, Luca Arnaboldi, Luca Pesce, Lenka Zdeborova, Florent Krzakala
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Computational Complexity of Finding Second-Order Stationary Points
Andreas Kontogiannis, Vasilis Pollatos, Sotiris Kanellopoulos, Panayotis Mertikopoulos, Aris Pagourtzis, Ioannis Panageas
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks
Songhua He, Periklis A. Papakonstantinou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Emergence of Reproducibility and Consistency in Diffusion Models
Huijie Zhang, Jinfan Zhou, Yifu Lu, Minzhe Guo, Peng Wang, Liyue Shen, Qing Qu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Entropy Enigma: Success and Failure of Entropy Minimization
Ori Press, Ravid Shwartz-Ziv, Yann Lecun, Matthias Bethge
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Expressive Power of Path-Based Graph Neural Networks
Caterina Graziani, Tamara Drucks, Fabian Jogl, Monica Bianchini, Franco Scarselli, Thomas Gärtner
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Fundamental Limits of Least-Privilege Learning
Theresa Stadler, Bogdan Kulynych, Michael Gastpar, Nicolas Papernot, Carmela Troncoso
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Good, The Bad, and Why: Unveiling Emotions in Generative AI
Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu, Xinyi Wang, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, Xing Xie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Illusion of State in State-Space Models
William Merrill, Jackson Petty, Ashish Sabharwal
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Linear Representation Hypothesis and the Geometry of Large Language Models
Kiho Park, Yo Joong Choe, Victor Veitch
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm
Giseung Park, Woohyeon Byeon, Seongmin Kim, Elad Havakuk, Amir Leshem, Youngchul Sung
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Merit of River Network Topology for Neural Flood Forecasting
Nikolas Kirschstein, Yixuan Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Non-linear $F$-Design and Applications to Interactive Learning
Alekh Agarwal, Jian Qian, Alexander Rakhlin, Tong Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Perception-Robustness Tradeoff in Deterministic Image Restoration
Guy Ohayon, Tomer Michaeli, Michael Elad
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks
Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, Antoni B. Chan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Pitfalls of Next-Token Prediction
Gregor Bachmann, Vaishnavh Nagarajan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Privacy Power of Correlated Noise in Decentralized Learning
Youssef Allouah, Anastasia Koloskova, Aymane El Firdoussi, Martin Jaggi, Rachid Guerraoui
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Relative Value of Prediction in Algorithmic Decision Making
Juan Carlos Perdomo
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Role of Learning Algorithms in Collective Action
Omri Ben-Dov, Jake Fawkes, Samira Samadi, Amartya Sanyal
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline
Haonan Wang, Qianli Shen, Yao Tong, Yang Zhang, Kenji Kawaguchi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling
Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning
Nathaniel Li, Alexander Pan, Anjali Gopal, Summer Yue, Daniel Berrios, Alice Gatti, Justin D. Li, Ann-Kathrin Dombrowski, Shashwat Goel, Gabriel Mukobi, Nathan Helm-Burger, Rassin Lababidi, Lennart Justen, Andrew Bo Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Ariel Herbert-Voss, Cort B Breuer, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Lin, Adam Alfred Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Ian Steneker, David Campbell, Brad Jokubaitis, Steven Basart, Stephen Fitz, Ponnurangam Kumaraguru, Kallol Krishna Karmakar, Uday Tupakula, Vijay Varadharajan, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, Dan Hendrycks
Machine Learning
日本大学: 慶應義塾大学
2024 · ICML
Theoretical Analysis of Learned Database Operations under Distribution Shift through Distribution Learnability
Sepanta Zeighami, Cyrus Shahabi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Theoretical insights for diffusion guidance: A case study for Gaussian mixture models
Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling
Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Thermometer: Towards Universal Calibration for Large Language Models
Maohao Shen, Subhro Das, Kristjan Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Think Before You Act: Decision Transformers with Working Memory
Jikun Kang, Romain Laroche, Xingdi Yuan, Adam Trischler, Xue Liu, Jie Fu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders
Zhiheng Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration
Gyusang Cho, Chan-Hyun Youn
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiers
Johann Schmidt, Sebastian Stober
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks
Stefano Sarao Mannelli, Yaraslau Ivashynka, Andrew M Saxe, Luca Saglietti
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Time Series Diffusion in the Frequency Domain
Jonathan Crabbé, Nicolas Huynh, Jan Pawel Stanczuk, Mihaela Van Der Schaar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Time Weaver: A Conditional Time Series Generation Model
Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin, Sujay Sanghavi, Sandeep P. Chinchali
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
Xiwen Chen, Peijie Qiu, Wenhui Zhu, Huayu Li, Hao Wang, Aristeidis Sotiras, Yalin Wang, Abolfazl Razi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
Jiaxiang Dong, Haixu Wu, Yuxuan Wang, Yun-Zhong Qiu, Li Zhang, Jianmin Wang, Mingsheng Long
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TimeX++: Learning Time-Series Explanations with Information Bottleneck
Zichuan Liu, Tianchun Wang, Jimeng Shi, Xu Zheng, Zhuomin Chen, Lei Song, Wenqian Dong, Jayantha Obeysekera, Farhad Shirani, Dongsheng Luo
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li, Xiangdong Huang, Jianmin Wang, Mingsheng Long
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge
Young D. Kwon, Rui Li, Stylianos Venieris, Jagmohan Chauhan, Nicholas Donald Lane, Cecilia Mascolo
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO
Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models
George-Octavian Bărbulescu, Peter Triantafillou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
To the Max: Reinventing Reward in Reinforcement Learning
Grigorii Veviurko, Wendelin Boehmer, Mathijs De Weerdt
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models
Mingjia Huo, Sai Ashish Somayajula, Youwei Liang, Ruisi Zhang, Farinaz Koushanfar, Pengtao Xie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Token-level Direct Preference Optimization
Yongcheng Zeng, Guoqing Liu, Weiyu Ma, Ning Yang, Haifeng Zhang, Jun Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Topological Neural Networks go Persistent, Equivariant, and Continuous
Yogesh Verma, Amauri H Souza, Vikas Garg
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Total Variation Distance Meets Probabilistic Inference
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Total Variation Floodgate for Variable Importance Inference in Classification
Wenshuo Wang, Lucas Janson, Lihua Lei, Aaditya Ramdas
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Toward Adaptive Reasoning in Large Language Models with Thought Rollback
Sijia Chen, Baochun Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Toward Availability Attacks in 3D Point Clouds
Yifan Zhu, Yibo Miao, Yinpeng Dong, Xiao-Shan Gao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components
Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low
Machine Learning
日本大学: 関与なし（対象大学）