Most Cited ICML "patl model-checking" Papers
5,975 papers found • Page 18 of 30
Conference
Stacking Deep Set Networks and Pooling by Quantiles
Zhuojun Chen, Xinghua Zhu, Dongzhe Su et al.
What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks
Xingwu Chen, Difan Zou
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks
Zhiyuan Cheng, Zhaoyi Liu, Tengda Guo et al.
GaussianPro: 3D Gaussian Splatting with Progressive Propagation
Kai Cheng, Xiaoxiao Long, Kaizhi Yang et al.
Kernel Semi-Implicit Variational Inference
Ziheng Cheng, Longlin Yu, Tianyu Xie et al.
Creative Text-to-Audio Generation via Synthesizer Programming
Manuel Cherep, Nikhil Singh, Jessica Shand
MS-TIP: Imputation Aware Pedestrian Trajectory Prediction
Pranav Singh Chib, Achintya Nath, Paritosh Kabra et al.
Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters
Brian Cho, Yaroslav Mukhin, Kyra Gan et al.
Hard Tasks First: Multi-Task Reinforcement Learning Through Task Scheduling
MYUNG-SIK CHO, Jong Eui Park, Suyoung Lee et al.
KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation
Minsik Cho, Mohammad Rastegari, Devang Naik
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Listwise Reward Estimation for Offline Preference-based Reinforcement Learning
Heewoong Choi, Sangwon Jung, Hongjoon Ahn et al.
A connection between Tempering and Entropic Mirror Descent
Nicolas Chopin, Francesca R Crucinio, Anna Korba
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts
Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui et al.
How Private are DP-SGD Implementations?
Lynn Chua, Badih Ghazi, Pritish Kamath et al.
Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens
Ross Clarke, Jose Miguel Hernandez-Lobato
Improving Token-Based World Models with Parallel Observation Prediction
Lior Cohen, Kaixin Wang, Bingyi Kang et al.
A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering
Vincent Cohen-Addad, Tommaso d'Orsi, Aida Mousavifar
Dynamic Correlation Clustering in Sublinear Update Time
Vincent Cohen-Addad, Silvio Lattanzi, Andreas Maggiori et al.
Conformal Prediction Sets Improve Human Decision Making
Jesse Cresswell, yi sui, Bhargava Kumar et al.
Position: Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis
Jessica Dai
Multi-View Clustering by Inter-cluster Connectivity Guided Reward
Hao Dai, Yang Liu, Peng Su et al.
High-Order Contrastive Learning with Fine-grained Comparative Levels for Sparse Ordinal Tensor Completion
Yu Dai, Junchen Shen, Zijie Zhai et al.
Boosting Offline Optimizers with Surrogate Sensitivity
Cuong Dao, Phi Le Nguyen, Thao Nguyen Truong et al.
Test-Time Degradation Adaptation for Open-Set Image Restoration
Yuanbiao Gou, Haiyu Zhao, Boyun Li et al.
A decoder-only foundation model for time-series forecasting
Abhimanyu Das, Weihao Kong, Rajat Sen et al.
Global Reinforcement Learning : Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods
Riccardo De Santi, Manish Prajapat, Andreas Krause
Predicting Lagrangian Multipliers for Mixed Integer Linear Programs
Francesco Demelas, Joseph Roux, Mathieu Lacroix et al.
An Unsupervised Approach for Periodic Source Detection in Time Series
Berken Utku Demirel, Christian Holz
Network Tight Community Detection
Jiayi Deng, Xiaodong Yang, Jun Yu et al.
Multicalibration for Confidence Scoring in LLMs
Gianluca Detommaso, Martin A Bertran, Riccardo Fogliato et al.
Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies
Alex DeWeese, Guannan Qu
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
Fast Co-Training under Weak Dependence via Stream-Based Active Learning
Ilias Diakonikolas, Mingchen Ma, Lisheng Ren et al.
Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization
Li Ding, Jenny Zhang, Jeff Clune et al.
Consistent Adversarially Robust Linear Classification: Non-Parametric Setting
Elvis Dohmatob
Precise Accuracy / Robustness Tradeoffs in Regression: Case of General Norms
Elvis Dohmatob, Meyer Scetbon
Impact of Decentralized Learning on Player Utilities in Stackelberg Games
Kate Donahue, Nicole Immorlica, Meena Jagadeesan et al.
Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective
Yuxin Dong, Tieliang Gong, Hong Chen et al.
Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models
Peijie Dong, Lujun Li, Zhenheng Tang et al.
Position: Building Guardrails for Large Language Models Requires Systematic Design
Yi DONG, Ronghui Mu, Gaojie Jin et al.
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
Jiaxiang Dong, Haixu Wu, Yuxuan Wang et al.
Spike Distance Function as a Learning Objective for Spike Prediction
Kevin Doran, Marvin Seifert, Carola Yovanovich et al.
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
Alexandre Drouin, Maxime Gasse, Massimo Caccia et al.
Principled Gradient-Based MCMC for Conditional Sampling of Text
Li Du, Afra Amini, Lucas Torroba Hennigen et al.
Position: Compositional Generative Modeling: A Single Model is Not All You Need
Yilun Du, Leslie Kaelbling
Improving Factuality and Reasoning in Language Models through Multiagent Debate
Yilun Du, Shuang Li, Antonio Torralba et al.
Learning Iterative Reasoning through Energy Diffusion
Yilun Du, Jiayuan Mao, Josh Tenenbaum
MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series
Jufang Duan, Wei Zheng, Yangzhou Du et al.
Unveiling the Potential of AI for Nanomaterial Morphology Prediction
Ivan Dubrovsky, Andrei Dmitrenko, Aleksey Dmitrenko et al.
Barrier Algorithms for Constrained Non-Convex Optimization
Pavel Dvurechenskii, Mathias Staudigl
Equivariant Frames and the Impossibility of Continuous Canonicalization
Nadav Dym, Hannah Lawrence, Jonathan Siegel
Efficient Error Certification for Physics-Informed Neural Networks
Francisco Eiras, Adel Bibi, Rudy Bunel et al.
Scalable Pre-training of Large Autoregressive Image Models
Alaaeldin Ali, Michal Klein, Shuangfei Zhai et al.
TSLANet: Rethinking Transformers for Time Series Representation Learning
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen et al.
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
Mohamed Elsayed, Homayoon Farrahi, Felix Dangel et al.
PAC-Bayesian Error Bound, via Rényi Divergence, for a Class of Linear Time-Invariant State-Space Models
Deividas Eringis, john leth, Zheng-Hua Tan et al.
Model Alignment as Prospect Theoretic Optimization
Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff et al.
Revisit the Essence of Distilling Knowledge through Calibration
Wen-Shu Fan, Su Lu, Xin-Chun Li et al.
DOGE: Domain Reweighting with Generalization Estimation
Simin Fan, Matteo Pagliardini, Martin Jaggi
Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
Luyang Fang, Yongkai Chen, Wenxuan Zhong et al.
Exploring Correlations of Self-Supervised Tasks for Graphs
Taoran Fang, Wei Chow, Yifei Sun et al.
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Jesse Farebrother, Jordi Orbay, Quan Vuong et al.
From Geometry to Causality- Ricci Curvature and the Reliability of Causal Inference on Networks
Amirhossein Farzam, Allen Tannenbaum, Guillermo Sapiro
Resisting Stochastic Risks in Diffusion Planners with the Trajectory Aggregation Tree
Lang Feng, Pengjie Gu, Bo An et al.
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Shikun Feng, Yuyan Ni, Li et al.
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
Shanglun Feng, Florian Tramer
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
Songtao Feng, Ming Yin, Yu-Xiang Wang et al.
Critical feature learning in deep neural networks
Kirsten Fischer, Javed Lindner, David Dahmen et al.
Explaining Probabilistic Models with Distributional Values
Luca Franceschi, Michele Donini, Cedric Archambeau et al.
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift
Luca Franco, Paolo Mandica, Konstantinos Kallidromitis et al.
Weisfeiler-Leman at the margin: When more expressivity matters
Billy Franks, Christopher Morris, Ameya Velingker et al.
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
Kevin Frans, Seohong Park, Pieter Abbeel et al.
Trust the Model Where It Trusts Itself - Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption
Bernd Frauenknecht, Artur Eisele, Devdutt Subhasish et al.
Trustworthy Actionable Perturbations
Jesse Friedbaum, Sudarshan Adiga, Ravi Tandon
Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
Wenzhi Gao, Qi Deng
Non-convex Stochastic Composite Optimization with Polyak Momentum
Yuan Gao, Anton Rodomanov, Sebastian Stich
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
Ziqi Gao, Qichao Wang, Aochuan Chen et al.
Fast-Slow Test-Time Adaptation for Online Vision-and-Language Navigation
JUNYU GAO, Xuan Yao, Changsheng Xu
Don't trust your eyes: on the (un)reliability of feature visualizations
Robert Geirhos, Roland S. Zimmermann, Blair Bilodeau et al.
Graph-Triggered Rising Bandits
Gianmarco Genalti, Marco Mussi, Nicola Gatti et al.
Reinforcement Learning within Tree Search for Fast Macro Placement
Zijie Geng, Jie Wang, Ziyan Liu et al.
Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models
Asma Ghandeharioun, Avi Caciularu, Adam Pearce et al.
Optimal Eye Surgeon: Finding image priors through sparse generators at initialization
Avrajit Ghosh, Xitong Zhang, Kenneth Sun et al.
CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
JUNCHAO GONG, LEI BAI, Peng Ye et al.
Does Label Smoothing Help Deep Partial Label Learning?
Xiuwen Gong, Nitin Bisht, Guandong Xu
AST-T5: Structure-Aware Pretraining for Code Generation and Understanding
Linyuan Gong, Mostafa Elhoushi, Alvin Cheung
Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks
Linyuan Gong, Sida Wang, Mostafa Elhoushi et al.
E$^2$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation
Yifan Gong, Zheng Zhan, Qing Jin et al.
Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates
Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo
Fine-grained Classes and How to Find Them
Matej Grcic, Artyom Gadetsky, Maria Brbic
Scaling Down Deep Learning with MNIST-1D
Sam Greydanus, Dmitry Kobak
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
Sebastian Gregor Gruber, Florian Buettner
EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization
Zhibin Gu, Zhendong Li, Songhe Feng
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Alex Gu, Baptiste Roziere, Hugh Leather et al.
On the Diminishing Returns of Width for Continual Learning
Etash Guha, Vihan Lakshman
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation
Gauthier Guinet, Behrooz Tehrani, Anoop Deoras et al.
DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
Siyuan Guo, Cheng Deng, Ying Wen et al.
Collaborative Heterogeneous Causal Inference Beyond Meta-analysis
Tianyu Guo, Sai Praneeth Karimireddy, Michael Jordan
FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering
Yongxin Guo, Xiaoying Tang, Tao Lin
Automated Loss function Search for Class-imbalanced Node Classification
Xinyu Guo, KAI WU, Xiaoyu Zhang et al.
GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks
Shivanshu Gupta, Clemens Rosenbaum, Ethan R. Elenberg
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
Jaehoon Hahm, Junho Lee, Sunghyun Kim et al.
Pursuing Overall Welfare in Federated Learning through Sequential Decision Making
Seok-Ju Hahn, Gi-Soo Kim, Junghye Lee
Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming
Hany Hamed, Subin Kim, Dongyeong Kim et al.
Riemannian coordinate descent algorithms on matrix manifolds
Andi Han, Pratik Kumar Jawanpuria, Bamdev Mishra
SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting
Lu Han, Han-Jia Ye, De-Chuan Zhan
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
Sungwon Han, Jinsung Yoon, Sercan Arik et al.
Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning
Jun-Yi Hang, Min-Ling Zhang
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training
Zhongkai Hao, Chang Su, LIU SONGMING et al.
Convergence Guarantees for the DeepWalk Embedding on Block Models
Christopher Harker, Aditya Bhaskara
Position: $C^*$-Algebraic Machine Learning $-$ Moving in a New Direction
Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri
MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation
Alexandre Hayderi, Amin Saberi, Ellen Vitercik et al.
LoRA+: Efficient Low Rank Adaptation of Large Models
Soufiane Hayou, Nikhil Ghosh, Bin Yu
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation
Zhenyu He, Guhao Feng, Shengjie Luo et al.
Domain-wise Data Acquisition to Improve Performance under Distribution Shift
Yue He, Dongbai Li, Pengfei Tian et al.
Ambiguity-Aware Abductive Learning
Hao-Yuan He, Hui Sun, Zheng Xie et al.
Understanding Diffusion Models by Feynman's Path Integral
Yuji Hirono, Akinori Tanaka, Kenji Fukushima
Estimating Unknown Population Sizes Using the Hypergeometric Distribution
Liam Hodgson, Danilo Bzdok
Two Tales of Single-Phase Contrastive Hebbian Learning
Rasmus Kjær Høier, Christopher Zach
Verifying message-passing neural networks via topology-based bounds tightening
Christopher Hojny, Shiqiang Zhang, Juan Campos et al.
Criterion Collapse and Loss Distribution Control
Matthew J. Holland
Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
Floris Holstege, Bram Wouters, Noud van Giersbergen et al.
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates
Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis et al.
Graph Neural PDE Solvers with Conservation and Similarity-Equivariance
Masanobu Horie, NAOTO MITSUME
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition
Samuel Horváth, Stefanos Laskaridis, Shashank Rajput et al.
Multi-Sender Persuasion: A Computational Perspective
Safwan Hossain, Tonghan Wang, Tao Lin et al.
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
Charlie Hou, Akshat Shrivastava, Hongyuan Zhan et al.
Careful with that Scalpel: Improving Gradient Surgery with an EMA
Yu-Guan Hsieh, James Thornton, Eugene Ndiaye et al.
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
Kyle Hsu, Jubayer Ibn Hamid, Kaylee Burns et al.
SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code
ziniu hu, Ahmet Iscen, Aashi Jain et al.
Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation
Dapeng Hu, Jian Liang, Xinchao Wang et al.
Improving Interpretation Faithfulness for Vision Transformers
Lijie Hu, Yixin Liu, Ninghao Liu et al.
Multigroup Robustness
Lunjia Hu, Charlotte Peale, Judy Hanwen Shen
High-Performance Temporal Reversible Spiking Neural Networks with $\mathcal{O}(L)$ Training Memory and $\mathcal{O}(1)$ Inference Cost
JiaKui Hu, Man Yao, Xuerui Qiu et al.
Accelerating Transformer Pre-training with 2:4 Sparsity
Yuezhou Hu, Kang Zhao, Weiyu Huang et al.
InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks
Xueyu Hu, Ziyu Zhao, Shuang Wei et al.
In-context Convergence of Transformers
Yu Huang, Yuan Cheng, Yingbin LIANG
Near-Linear Time Approximation Algorithms for k-means with Outliers
Junyu Huang, Qilong Feng, Ziyun Huang et al.
Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion
Yujia Huang, Adishree Ghatare, Yuanzhe Liu et al.
InstructSpeech: Following Speech Editing Instructions via Large Language Models
Rongjie Huang, Ruofan Hu, Yongqi Wang et al.
Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models
Ding Huang, Ting Li, Jian Huang
Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning
Zhuo Huang, Chang Liu, Yinpeng Dong et al.
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Wei Huang, Yangdong Liu, Haotong Qin et al.
An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series
Qiang Huang, Chuizheng Meng, Defu Cao et al.
On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective
Jincheng Huang, Jialie SHEN, Xiaoshuang Shi et al.
MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
Qian Huang, Jian Vora, Percy Liang et al.
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
Keke Huang, Yu Guang Wang, Ming Li et al.
Faster Adaptive Decentralized Learning Algorithms
Feihu Huang, jianyu zhao
Position: The Platonic Representation Hypothesis
Minyoung Huh, Brian Cheung, Tongzhou Wang et al.
Residual Quantization with Implicit Neural Codebooks
Iris Huijben, Matthijs Douze, Matthew Muckley et al.
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
Tom Huix, Anna Korba, Alain Oliviero Durmus et al.
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
Inwoo Hwang, Yunhyeok Kwak, Suhyung Choi et al.
Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control
Dongyoon Hwang, Byungkun Lee, Hojoon Lee et al.
PASOA- PArticle baSed Bayesian Optimal Adaptive design
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Attribution-based Explanations that Provide Recourse Cannot be Robust
Hidde Fokkema, Rianne de Heide, Tim van Erven
Learning to Reach Goals via Diffusion
Vineet Jain, Siamak Ravanbakhsh
An Independence-promoting Loss for Music Generation with Language Models
Jean-Marie Lemercier, Simon Rouard, Jade Copet et al.
Repeat After Me: Transformers are Better than State Space Models at Copying
Samy Jelassi, David Brandfonbrener, Sham Kakade et al.
Advancing Dynamic Sparse Training by Exploring Optimization Opportunities
Jie Ji, Gen Li, Lu Yin et al.
Towards Efficient Exact Optimization of Language Model Alignment
Haozhe Ji, Cheng Lu, Yilin Niu et al.
Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic
Tianying Ji, Yu Luo, Fuchun Sun et al.
Discrete Latent Perspective Learning for Segmentation and Detection
Deyi Ji, Feng Zhao, Lanyun Zhu et al.
Simulation-Based Inference with Quantile Regression
He Jia
Chain-of-Thought Predictive Control
Zhiwei Jia, Vineet Thumuluri, Fangchen Liu et al.
NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks
Haiyan Jiang, Giulia De Masi, Huan Xiong et al.
On the Origins of Linear Representations in Large Language Models
Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar et al.
Federated Optimization with Doubly Regularized Drift Correction
Xiaowen Jiang, Anton Rodomanov, Sebastian Stich
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization
Wei Jiang, Sifan Yang, Wenhao Yang et al.
SuDA: Support-based Domain Adaptation for Sim2Real Hinge Joint Tracking with Flexible Sensors
Fang Jiawei, Haishan Song, Chengxu Zuo et al.
What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement
Xisen Jin, Xiang Ren
An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran et al.
FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data
Shusen Jing, Anlan Yu, Shuai Zhang et al.
Graph Generation with Diffusion Mixture
Jaehyeong Jo, Dongki Kim, Sung Ju Hwang
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs
Daniel D. Johnson, Daniel Tarlow, David Duvenaud et al.
IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation
Taejong Joo, Diego Klabjan
Unsupervised Episode Generation for Graph Meta-learning
Jihyeong Jung, Sangwoo Seo, Sungwon Kim et al.
Replicable Learning of Large-Margin Halfspaces
Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen et al.
Tell, Don't Show: Language Guidance Eases Transfer Across Domains in Images and Videos
Tarun Kalluri, Bodhisattwa Prasad Majumder, Manmohan Chandraker
Neural Tangent Kernels for Axis-Aligned Tree Ensembles
Ryuichi Kanoh, Mahito Sugiyama
On the Generalization of Equivariant Graph Neural Networks
Rafał Karczewski, Amauri Souza, Vikas Garg
Progressive Inference: Explaining Decoder-Only Sequence Classification Models Using Intermediate Predictions
Sanjay Kariyappa, Freddy Lecue, Saumitra Mishra et al.
DUPLEX: Dual GAT for Complex Embedding of Directed Graphs
Zhaoru Ke, Hang Yu, Jianguo Li et al.
A Universal Transfer Theorem for Convex Optimization Algorithms Using Inexact First-order Oracles
Phillip Kerger, Marco Molinaro, Hongyi Jiang et al.
Neural Tangent Kernels Motivate Cross-Covariance Graphs in Neural Networks
Shervin Khalafi, Saurabh Sihag, Alejandro Ribeiro
Can Machines Learn the True Probabilities?
Jinsook Kim
LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging
Jinuk Kim, Marwa El Halabi, Mingi Ji et al.
CARTE: Pretraining and Transfer for Tabular Learning
Myung Jun Kim, Leo Grinsztajn, Gael Varoquaux
Active Label Correction for Semantic Segmentation with Foundation Models
Hoyoung Kim, SEHYUN HWANG, Suha Kwak et al.
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
Dongha Kim, Jaesung Hwang, Jongjin Lee et al.
Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs
Mingyu Kim, Kim Jun-Seong, Se-Young Yun et al.
Learning to Explore for Stochastic Gradient MCMC
SeungHyun Kim, Seohyeon Jung, SeongHyeon Kim et al.
Attribute Based Interpretable Evaluation Metrics for Generative Models
Dongkyun Kim, Mingi Kwon, Youngjung Uh
EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning
Jongsuk Kim, Hyeongkeun Lee, Kyeongha Rho et al.
Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning
Dongkwan Kim, Alice Oh
Privacy-Preserving Embedding via Look-up Table Evaluation with Fully Homomorphic Encryption
Jae-yun Kim, Saerom Park, Joohee Lee et al.
Polynomial-based Self-Attention for Table Representation Learning
Jayoung Kim, Yehjin Shin, Jeongwhan Choi et al.
Discovering Features with Synergistic Interactions in Multiple Views
Chohee Kim, M van der Schaar, Changhee Lee
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design
Leo Klarner, Tim G. J. Rudner, Garrett Morris et al.
Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes
Hyunouk Ko, Xiaoming Huo