ICML

2021–2025 確定版

著者一覧 · 国際会議 · 大学ランキング

ICML 公式サイト ↗

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
PAPM: A Physics-aware Proxy Model for Process Systems
Pengwei Liu, Zhongkai Hao, Xingyu Ren, Hangjie Yuan, Jiayang Ren, Dong Ni
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling
Phong C.H. Nguyen, Xinlun Cheng, Shahab Azarfar, Pradeep Seshadri, Yen T. Nguyen, Munho Kim, Sanghun Choi, H.S. Udaykumar, Stephen Baek
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition
Ziyang Zhang, Qizhen Zhang, Jakob Nicolaus Foerster
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PASOA- PArticle baSed Bayesian Optimal Adaptive design
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez, Florence Forbes
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Haitao Mao, Qian Chen, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation
Runze Liu, Yali Du, Fengshuo Bai, Jiafei Lyu, Xiu Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang, Hang Zhou, Jinsheng Huang, Wei Ju, Zhiping Xiao, Ming Zhang, Yizhou Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
Hyeong Kyu Choi, Yixuan Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PID: Prompt-Independent Data Protection Against Latent Diffusion Models
Ang Li, Yichuan Mo, Mingjie Li, Yisen Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PIDformer: Transformer Meets Control Theory
Tam Minh Nguyen, Cesar A Uribe, Tan Minh Nguyen, Richard Baraniuk
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling
Utsav Singh, Wesley A Suttle, Brian M. Sadler, Vinay P. Namboodiri, Amrit Bedi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
Soroush Nasiriany, Fei Xia, Wenhao Yu, Ted Xiao, Jacky Liang, Ishita Dasgupta, Annie Xie, Danny Driess, Ayzaan Wahid, Zhuo Xu, Quan Vuong, Tingnan Zhang, Tsang-Wei Edward Lee, Kuang-Huei Lee, Peng Xu, Sean Kirmani, Yuke Zhu, Andy Zeng, Karol Hausman, Nicolas Heess, Chelsea Finn, Sergey Levine, Brian Ichter
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching
Haitao Lin, Odin Zhang, Huifeng Zhao, Dejun Jiang, Lirong Wu, Zicheng Liu, Yufei Huang, Stan Z. Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé Iii, Furong Huang, Andrey Kolobov
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Pairwise Alignment Improves Graph Domain Adaptation
Shikun Liu, Deyu Zou, Han Zhao, Pan Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parallel Affine Transformation Tuning of Markov Chain Monte Carlo
Philip Schär, Michael Habeck, Daniel Rudolf
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parallelized Spatiotemporal Slot Binding for Videos
Gautam Singh, Yue Wang, Jiawei Yang, Boris Ivanovic, Sungjin Ahn, Marco Pavone, Tong Che
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
Xinyu Ma, Xu Chu, Zhibang Yang, Yang Lin, Xin Gao, Junfeng Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Phung
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations
Pan Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parameter-Efficient Fine-Tuning with Controls
Chi Zhang, Cheng Jingpu, Yanyu Xu, Qianxiao Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
Ziqi Gao, Qichao Wang, Aochuan Chen, Zijing Liu, Bingzhe Wu, Liang Chen, Jia Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parameterized Physics-informed Neural Networks for Parameterized PDEs
Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Parsimonious Learning-Augmented Approximations for Dense Instances of $\mathcalNP$-hard Problems
Evripidis Bampis, Bruno Escoffier, Michalis Xefteris
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling
Chengliang Liu, Gehui Xu, Jie Wen, Yabo Liu, Chao Huang, Yong Xu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Partial Optimality in the Linear Ordering Problem
David Stein, Bjoern Andres
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Partially Stochastic Infinitely Deep Bayesian Neural Networks
Sergio Calvo Ordoñez, Matthieu Meunier, Francesco Piatti, Yuantao Shi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Particle Denoising Diffusion Sampler
Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models
Asma Ghandeharioun, Avi Caciularu, Adam Pearce, Lucas Dixon, Mor Geva
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Path-Guided Particle-based Sampling
Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Pausing Policy Learning in Non-stationary Reinforcement Learning
Hyunin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PcLast: Discovering Plannable Continuous Latent States
Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam, Raihan Seraj, Yonathan Efroni, Lekan P Molu, Miroslav Dudı́k, John Langford, Alex Lamb
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning
Yibo Zhou, Hai-Miao Hu, Yirong Xiang, Xiaokang Zhang, Haotian Wu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams
Brian M Cho, Kyra Gan, Nathan Kallus
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PerceptAnon: Exploring the Human Perception of Image Anonymization Beyond Pseudonymization for GDPR
Kartik Patwari, Chen-Nee Chuah, Lingjuan Lyu, Vivek Sharma
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Perfect Alignment May be Poisonous to Graph Contrastive Learning
Jingyu Liu, Huayi Tang, Yong Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Performance Bounds for Active Binary Testing with Information Maximization
Aditya Chattopadhyay, Benjamin David Haeffele, Rene Vidal, Donald Geman
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Performative Prediction with Bandit Feedback: Learning through Reparameterization
Yatong Chen, Wei Tang, Chien-Ju Ho, Yang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Perturb-and-Project: Differentially Private Similarities and Marginals
Vincent Cohen-Addad, Tommaso D’Orsi, Alessandro Epasto, Vahab Mirrokni, Peilin Zhong
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Physics and Lie symmetry informed Gaussian processes
David Dalton, Dirk Husmeier, Hao Gao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
Zeyuan Allen-Zhu, Yuanzhi Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification
Yiming Meng, Ruikun Zhou, Amartya Mukherjee, Maxwell Fitzsimmons, Christopher Song, Jun Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Pi-DUAL: Using privileged information to distinguish clean from noisy labels
Ke Wang, Guillermo Ortiz-Jimenez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou, Pascal Frossard
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach
Mim Van Den Bos, Jacobus G. M. Van Der Linden, Emir Demirović
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PinNet: Pinpoint Instructive Information for Retrieval Augmented Code-to-Text Generation
Han Fu, Jian Tan, Pinhan Zhang, Feifei Li, Jianling Sun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
Chang Chen, Junyeob Baek, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Planning, Fast and Slow: Online Reinforcement Learning with Action-Free Offline Data via Multiscale Planners
Chengjie Wu, Hao Hu, Yiqin Yang, Ning Zhang, Chongjie Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Plug-and-Play image restoration with Stochastic deNOising REgularization
Marien Renaud, Jean Prost, Arthur Leclaire, Nicolas Papadakis
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Plug-in Performative Optimization
Licong Lin, Tijana Zrnic
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Pluvial Flood Emulation with Hydraulics-informed Message Passing
Arnold Kazadi, James Doss-Gollin, Arlei Lopes Da Silva
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PointMC: Multi-instance Point Cloud Registration based on Maximal Cliques
Yue Wu, Xidao Hu, Yongzhe Yuan, Xiaolong Fan, Maoguo Gong, Hao Li, Mingyang Zhang, Qiguang Miao, Wenping Ma
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Policy Evaluation for Variance in Average Reward Reinforcement Learning
Shubhada Agrawal, Prashanth L A, Siva Theja Maguluri
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Policy Learning for Balancing Short-Term and Long-Term Rewards
Peng Wu, Ziyu Shen, Feng Xie, Wang Zhongyao, Chunchen Liu, Yan Zeng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Policy-conditioned Environment Models are More Generalizable
Ruifeng Chen, Xiong-Hui Chen, Yihao Sun, Siyuan Xiao, Minhui Li, Yang Yu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels
Praneeth Kacham, Vahab Mirrokni, Peilin Zhong
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Polynomial-based Self-Attention for Table Representation Learning
Jayoung Kim, Yehjin Shin, Jeongwhan Choi, Hyowon Wi, Noseong Park
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: $C^*$-Algebraic Machine Learning $-$ Moving in a New Direction
Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: A Call for Embodied AI
Giuseppe Paolo, Jonas Gonzalez-Billandon, Balázs Kégl
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: A Call to Action for a Human-Centered AutoML Paradigm
Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede, Andreas C Mueller, Frank Hutter, Matthias Feurer, Bernd Bischl
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: A Roadmap to Pluralistic Alignment
Taylor Sorensen, Jared Moore, Jillian Fisher, Mitchell L Gordon, Niloofar Mireshghallah, Christopher Michael Rytting, Andre Ye, Liwei Jiang, Ximing Lu, Nouha Dziri, Tim Althoff, Yejin Choi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: A Safe Harbor for AI Evaluation and Red Teaming
Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Alex Pentland, Arvind Narayanan, Percy Liang, Peter Henderson
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research
Riley Simmons-Edler, Ryan Paul Badman, Shayne Longpre, Kanaka Rajan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: AI/ML Influencers Have a Place in the Academic Process
Iain Weissburg, Mehir Arora, Xinyi Wang, Liangming Pan, William Yang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Amazing Things Come From Having Many Good Models
Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo Seltzer, Ronald Parr, Jiachang Liu, Srikar Katta, Jon Donnelly, Harry Chen, Zachery Boner
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Martina G. Vilas, Federico Adolfi, David Poeppel, Gemma Roig
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Application-Driven Innovation in Machine Learning
David Rolnick, Alan Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Automatic Environment Shaping is the Next Frontier in RL
Younghyo Park, Gabriel B. Margolis, Pulkit Agrawal
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Benchmarking is Limited in Reinforcement Learning Research
Scott M. Jordan, Adam White, Bruno Castro Da Silva, Martha White, Philip S. Thomas
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis
Jessica Dai
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Building Guardrails for Large Language Models Requires Systematic Design
Yi Dong, Ronghui Mu, Gaojie Jin, Yi Qi, Jinwei Hu, Xingyu Zhao, Jie Meng, Wenjie Ruan, Xiaowei Huang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
Bruno Gavranović, Paul Lessard, Andrew Joseph Dudzik, Tamara Von Glehn, João Guilherme Madeira Araújo, Petar Veličković
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Compositional Generative Modeling: A Single Model is Not All You Need
Yilun Du, Leslie Pack Kaelbling
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
Florian Tramèr, Gautam Kamath, Nicholas Carlini
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
Golnoosh Farnadi, Mohammad Havaei, Negar Rostamzadeh
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?
Shayne Longpre, Robert Mahari, Naana Obeng-Marnu, William Brannon, Tobin South, Katy Ilonka Gero, Alex Pentland, Jad Kabbara
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Data-driven Discovery with Large Generative Models
Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Sanchaita Hazra, Ashish Sabharwal, Peter Clark
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Do Not Explain Vision Models Without Context
Paulina Tomaszewska, Przemyslaw Biecek
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Do pretrained Transformers Learn In-Context by Gradient Descent?
Lingfeng Shen, Aayush Mishra, Daniel Khashabi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Embracing Negative Results in Machine Learning
Florian Karl, Malte Kemeter, Gabriel Dax, Paulina Sierak
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Enforced Amnesia as a Way to Mitigate the Potential Risk of Silent Suffering in the Conscious AI
Yegor Tkachenko
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Evolving AI Collectives Enhance Human Diversity and Enable Self-Regulation
Shiyang Lai, Yujin Potter, Junsol Kim, Richard Zhuang, Dawn Song, James Evans
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Explain to Question not to Justify
Przemyslaw Biecek, Wojciech Samek
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training
Lin Lu, Chenxi Dai, Wangcheng Tao, Binhang Yuan, Yanan Sun, Pan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Foundation Agents as the Paradigm Shift for Decision Making
Xiaoqian Liu, Xingzhou Lou, Jianbin Jiao, Junge Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches
David Glukhov, Ilia Shumailov, Yarin Gal, Nicolas Papernot, Vardan Papyan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Future Directions in the Theory of Graph Machine Learning
Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Graph Foundation Models Are Already Here
Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Insights from Survey Methodology can Improve Training Data
Stephanie Eckman, Barbara Plank, Frauke Kreuter
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Intent-aligned AI Systems Must Optimize for Agency Preservation
Catalin Mitelut, Benjamin Smith, Peter Vamplew
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Is machine learning good or bad for the natural sciences?
David W Hogg, Soledad Villar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Key Claims in LLM Research Have a Long Tail of Footnotes
Anna Rogers, Sasha Luccioni
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks
Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, Mudit Verma, Kaya Stechly, Siddhant Bhambri, Lucas Paul Saldyt, Anil B Murthy
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Levels of AGI for Operationalizing Progress on the Path to AGI
Meredith Ringel Morris, Jascha Sohl-Dickstein, Noah Fiedel, Tris Warkentin, Allan Dafoe, Aleksandra Faust, Clement Farabet, Shane Legg
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Leverage Foundational Models for Black-Box Optimization
Xingyou Song, Yingtao Tian, Robert Tjarko Lange, Chansoo Lee, Yujin Tang, Yutian Chen
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Machine Learning-powered Assessments of the EU Digital Services Act Aid Quantify Policy Impacts on Online Harms
Eleonora Bonel, Luca Nannini, Davide Bassi, Michele Joshua Maggini
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Measure Dataset Diversity, Don’t Just Claim It
Dora Zhao, Jerone Andrews, Orestis Papakyriakopoulos, Alice Xiang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Position: Mission Critical – Satellite Data is a Distinct Modality in Machine Learning
Esther Rolf, Konstantin Klemmer, Caleb Robinson, Hannah Kerner
Machine Learning
日本大学: 関与なし（対象大学）