Most Cited ICML "compute-optimal training" Papers
5,975 papers found • Page 24 of 30
Conference
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
Sungmin Cha, Kyunghyun Cho, Taesup Moon
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
Liangzu Peng, Wotao Yin
Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference
Yujin Han, Difan Zou
Effective Federated Graph Matching
Yang Zhou, Zijie Zhang, Zeru Zhang et al.
Self-cognitive Denoising in the Presence of Multiple Noisy Label Sources
Yi-Xuan Sun, Ya-Lin Zhang, BIN HAN et al.
Explaining Graph Neural Networks via Structure-aware Interaction Index
Ngoc Bui, Trung Hieu Nguyen, Viet Anh Nguyen et al.
GliDe with a CaPE: A Low-Hassle Method to Accelerate Speculative Decoding
Cunxiao Du, Jing Jiang, Xu Yuanchen et al.
Generative Conditional Distributions by Neural (Entropic) Optimal Transport
Bao Nguyen, Binh Nguyen, Trung Hieu Nguyen et al.
Federated Continual Learning via Prompt-based Dual Knowledge Transfer
Hongming Piao, Yichen WU, Dapeng Wu et al.
An Interpretable Evaluation of Entropy-based Novelty of Generative Models
Jingwei Zhang, Cheuk Ting Li, Farzan Farnia
xT: Nested Tokenization for Larger Context in Large Images
Ritwik Gupta, Shufan Li, Tyler Zhu et al.
Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes
Jaehyeong Jo, Sung Ju Hwang
Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
Xutong Liu, Siwei Wang, Jinhang Zuo et al.
SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation
Junjie Zhang, Chenjia Bai, Haoran He et al.
Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization
Feihu Huang
Easing Concept Bleeding in Diffusion via Entity Localization and Anchoring
Jiewei Zhang, Song Guo, Peiran Dong et al.
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition
Shikai Fang, Qingsong Wen, Yingtao Luo et al.
Toward Adaptive Reasoning in Large Language Models with Thought Rollback
Sijia Chen, Baochun Li
When Will Gradient Regularization Be Harmful?
Yang Zhao, Hao Zhang, Xiuyuan Hu
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
Langzhang Liang, Sunwoo Kim, Kijung Shin et al.
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
Tara Akhound-Sadegh, Jarrid Rector-Brooks, Joey Bose et al.
Privacy Profiles for Private Selection
Antti Koskela, Rachel Redberg, Yu-Xiang Wang
From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning
Wei Chen, Zhen Huang, Liang Xie et al.
Improving Neural Logic Machines via Failure Reflection
Zhiming Li, Yushi Cao, Yan Zheng et al.
Less is More: on the Over-Globalizing Problem in Graph Transformers
Yujie Xing, Xiao Wang, Yibo Li et al.
Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
Yexin Zhang, Chenyi Zhang, Cong Fang et al.
Stochastic Localization via Iterative Posterior Sampling
Louis Grenioux, Maxence Noble, Marylou Gabrié et al.
Learning Modality Knowledge Alignment for Cross-Modality Transfer
Wenxuan Ma, Shuang Li, Lincan Cai et al.
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
Xiaochuan Gong, Jie Hao, Mingrui Liu
Differentiable Model Scaling using Differentiable Topk
Kai Liu, Ruohui Wang, Jianfei Gao et al.
Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic
Nicolas Alder, Ralf Herbrich
LoRA Training in the NTK Regime has No Spurious Local Minima
Uijeong Jang, Jason Lee, Ernest Ryu
Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique
TaeHo Yoon, Jaeyeon (Jay) Kim, Jaewook Suh et al.
Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective
Junwei Yang, Kangjie Zheng, Siyu Long et al.
ESM All-Atom: Multi-Scale Protein Language Model for Unified Molecular Modeling
Kangjie Zheng, Siyu Long, Tianyu Lu et al.
Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models
Mina Dalirrooyfard, Konstantin Makarychev, Slobodan Mitrovic
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis
Luyuan Xie, Manqing Lin, Tianyu Luan et al.
Differentially Private Decentralized Learning with Random Walks
Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay
Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning
Takayuki Osa, Tatsuya Harada
Towards Resource-friendly, Extensible and Stable Incomplete Multi-view Clustering
Shengju Yu, Dong Zhibin, Siwei Wang et al.
Adaptive Robust Learning using Latent Bernoulli Variables
Aleksandr Karakulev, Dave Zachariah, Prashant Singh
Confidence Aware Inverse Constrained Reinforcement Learning
Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi et al.
Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation
Weixuan Liang, En Zhu, Shengju Yu et al.
Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information
Xinhang Wan, Jiyuan Liu, Xinwang Liu et al.
Solving Poisson Equations using Neural Walk-on-Spheres
Hong Chul Nam, Julius Berner, Anima Anandkumar
Mean-field Underdamped Langevin Dynamics and its Spacetime Discretization
Qiang Fu, Ashia Wilson
DoRA: Weight-Decomposed Low-Rank Adaptation
Shih-Yang Liu, Chien-Yi Wang, Hongxu Yin et al.
Flextron: Many-in-One Flexible Large Language Model
Ruisi Cai, Saurav Muralidharan, Greg Heinrich et al.
Bayesian Exploration Networks
Mattie Fellows, Brandon Kaplowitz, Christian Schroeder de Witt et al.
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers
Brian Chen, Tianyang Hu, Hui Jin et al.
MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark
Dongping Chen, Ruoxi Chen, Shilin Zhang et al.
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
Shirin Shoushtari, JIAMING LIU, Edward Chandler et al.
DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning
Jianxiong Li, Jinliang Zheng, Yinan Zheng et al.
Learning to Compile Programs to Neural Networks
Logan Weber, Jesse Michel, Alex Renda et al.
FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees
Jiahao Liu, Yipeng Zhou, Di Wu et al.
ELF: Encoding Speaker-Specific Latent Speech Feature for Speech Synthesis
Jungil Kong, Junmo Lee, Jeongmin Kim et al.
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
Ye Tian, Haolei Weng, Yang Feng
SAPG: Split and Aggregate Policy Gradients
Jayesh Singla, Ananye Agarwal, Deepak Pathak
Attack-free Evaluating and Enhancing Adversarial Robustness on Categorical Data
Yujun Zhou, Yufei Han, Haomin Zhuang et al.
Bridging Environments and Language with Rendering Functions and Vision-Language Models
Théo Cachet, Christopher Dance, Olivier Sigaud
MoMo: Momentum Models for Adaptive Learning Rates
Fabian Schaipp, Ruben Ohana, Michael Eickenberg et al.
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
Brooks(Ruijia) Niu, Dongxia Wu, Kai Kim et al.
Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts
Zhi-Yi Chin, Chieh Ming Jiang, Ching-Chun Huang et al.
Fine-grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention
Aaron Havens, Alexandre Araujo, Huan Zhang et al.
Gambling-Based Confidence Sequences for Bounded Random Vectors
Jongha (Jon) Ryu, Gregory Wornell
Operator SVD with Neural Networks via Nested Low-Rank Approximation
Jongha (Jon) Ryu, Xiangxiang Xu, Hasan Sabri Melihcan Erol et al.
Offline Actor-Critic Reinforcement Learning Scales to Large Models
Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang et al.
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
Jonas Schweisthal, Dennis Frauen, M van der Schaar et al.
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
MoonJeong Park, Jaeseung Heo, Dongwoo Kim
Hypergraph-enhanced Dual Semi-supervised Graph Classification
Wei Ju, Zhengyang Mao, Siyu Yi et al.
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers
Muhammed Emrullah Ildiz, Yixiao HUANG, Yingcong Li et al.
Online Linear Regression in Dynamic Environments via Discounting
Andrew Jacobsen, Ashok Cutkosky
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang et al.
Uncertainty for Active Learning on Graphs
Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier et al.
Decomposing and Editing Predictions by Modeling Model Computation
Harshay Shah, Andrew Ilyas, Aleksander Madry
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 et al.
Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs
Luca Arnaboldi, Yatin Dandi, FLORENT KRZAKALA et al.
Asymptotics of feature learning in two-layer networks after one gradient-step
Hugo Cui, Luca Pesce, Yatin Dandi et al.
Initial Guessing Bias: How Untrained Networks Favor Some Classes
Emanuele Francazi, Aurelien Lucchi, Marco Baity-Jesi
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks
Dongyoung Lim, Sotirios Sabanis
Taylor Videos for Action Recognition
Lei Wang, Xiuyuan Yuan, Tom Gedeon et al.
On Statistical Learning Theory for Distributional Inputs
Christian Fiedler, Pierre-François Massiani, Friedrich Solowjow et al.
Structure-based drug design by denoising voxel grids
Pedro O. Pinheiro, Arian Jamasb, Omar Mahmood et al.
Towards Realistic Model Selection for Semi-supervised Learning
Muyang Li, Xiaobo Xia, Runze Wu et al.
On the Second-Order Convergence of Biased Policy Gradient Algorithms
Siqiao Mu, Diego Klabjan
Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation
Rahul Singh, Akshay Mete, Avik Kar et al.
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs et al.
A Unified View of FANOVA: A Comprehensive Bayesian Framework for Component Selection and Estimation
Yosra MARNISSI, Maxime Leiber
Non-parametric Online Change Point Detection on Riemannian Manifolds
Xiuheng Wang, Ricardo Borsoi, Cédric Richard
On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation
Álvaro Labarca Silva, Denis Parra, Rodrigo A Toro Icarte
DFlow: A Generative Model Combining Denoising AutoEncoder and Normalizing Flow for High Fidelity Waveform Generation
Chenfeng Miao, Qingying Zhu, Chen Minchuan et al.
On Online Experimentation without Device Identifiers
Shiv Shankar, Ritwik Sinha, Madalina Fiterau
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization
Yang Jin, Zhicheng Sun, Kun Xu et al.
SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
Tianshu Chu, Dachuan Xu, Wei Yao et al.
Transferable Facial Privacy Protection against Blind Face Restoration via Domain-Consistent Adversarial Obfuscation
Kui Zhang, Hang Zhou, Jie Zhang et al.
HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
Mantas Mazeika, Long Phan, Xuwang Yin et al.
Emergent Equivariance in Deep Ensembles
Jan Gerken, Pan Kessel
Do Efficient Transformers Really Save Computation?
Kai Yang, Jan Ackermann, Zhenyu He et al.
Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
Aditya A. Ramesh, Kenny Young, Louis Kirsch et al.
GPTSwarm: Language Agents as Optimizable Graphs
Mingchen Zhuge, Wenyi Wang, Louis Kirsch et al.
Provably Robust DPO: Aligning Language Models with Noisy Feedback
Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan
Balanced Resonate-and-Fire Neurons
Saya Higuchi, Sebastian Kairat, Sander Bohte et al.
Path-Guided Particle-based Sampling
Mingzhou Fan, Ruida Zhou, Chao Tian et al.
GFlowNet Training by Policy Gradients
Puhua Niu, Shili Wu, Mingzhou Fan et al.
Logistic Variational Bayes Revisited
Michael Komodromos, Marina Evangelou, Sarah Filippi
Cross-domain Open-world Discovery
Shuo Wen, Maria Brbic
Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers
Yuxing Liu, Lesi Chen, Luo Luo
Fewer Truncations Improve Language Modeling
Hantian Ding, Zijian Wang, Giovanni Paolini et al.
Nesting Particle Filters for Experimental Design in Dynamical Systems
Sahel Iqbal, Adrien Corenflos, Simo Särkkä et al.
An Information-Theoretic Analysis of In-Context Learning
Hong Jun Jeon, Jason Lee, Qi Lei et al.
Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection
Abhinab Acharya, Dayou Yu, Qi Yu et al.
Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
Tenglong Liu, Yang Li, Yixing Lan et al.
Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference
Luca Masserano, Alexander Shen, Michele Doro et al.
A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models
Taehong Moon, Moonseok Choi, EungGu Yun et al.
Beyond the Norms: Detecting Prediction Errors in Regression Models
Andres Altieri, Marco Romanelli, Georg Pichler et al.
Improving Open-Ended Text Generation via Adaptive Decoding
Wenhong Zhu, Hongkun Hao, Zhiwei He et al.
A New Robust Partial p-Wasserstein-Based Metric for Comparing Distributions
Sharath Raghvendra, Pouyan Shirzadian, Kaiyi Zhang
Fast Timing-Conditioned Latent Audio Diffusion
Zach Evans, CJ Carr, Josiah Taylor et al.
Overcoming the Optimizer's Curse: Obtaining Realistic Prescriptions from Neural Networks
Asterios Tsiourvas, Georgia Perakis
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts
Ha Manh Bui, Anqi Liu
Causal Inference out of Control: Estimating Performativity without Treatment Randomization
Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
Differentiability and Optimization of Multiparameter Persistent Homology
Luis Scoccola, Siddharth Setlur, David Loiseaux et al.
Hybrid Inverse Reinforcement Learning
Juntao Ren, Gokul Swamy, Steven Wu et al.
Cooperative Graph Neural Networks
Ben Finkelshtein, Xingyue Huang, Michael Bronstein et al.
Generalization to New Sequential Decision Making Tasks with In-Context Learning
Sharath Chandra Raparthy, Eric Hambro, Robert Kirk et al.
Allocation Requires Prediction Only if Inequality Is Low
Ali Shirali, Rediet Abebe, Moritz Hardt
Latent Space Symmetry Discovery
Jianke Yang, Nima Dehmamy, Robin Walters et al.
Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?
Yilong Wang, Haishan Ye, Guang Dai et al.
Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification
Jay Gala, Pengtao Xie
Data-free Neural Representation Compression with Riemannian Neural Dynamics
Zhengqi Pei, Anran Zhang, Shuhui Wang et al.
FlowMM: Generating Materials with Riemannian Flow Matching
Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram et al.
Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
Neta Shaul, Uriel Singer, Ricky T. Q. Chen et al.
Variational Schrödinger Diffusion Models
Wei Deng, Weijian Luo, Yixin Tan et al.
Improving Transformers with Dynamically Composable Multi-Head Attention
Da Xiao, Qingye Meng, Shengping Li et al.
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
Haoyang Zheng, Hengrong Du, Qi Feng et al.
Learning Universal Predictors
Jordi Grau-Moya, Tim Genewein, Marcus Hutter et al.
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
Guy Bar Shalom, Beatrice Bevilacqua, Haggai Maron
Efficient Exploration for LLMs
Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao et al.
Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors
Chun-Yin Huang, Kartik Srinivas, Xin Zhang et al.
Amortizing Pragmatic Program Synthesis with Rankings
Yewen Pu, Saujas Vaduguru, Priyan Vaithilingam et al.
Memoria: Resolving Fateful Forgetting Problem through Human-Inspired Memory Architecture
Sangjun Park, JinYeong Bak
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks
Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi et al.
Surprisingly Strong Performance Prediction with Neural Graph Features
Gabriela Kadlecová, Jovita Lukasik, Martin Pilát et al.
Stability and Multigroup Fairness in Ranking with Uncertain Predictions
Siddartha Devic, Aleksandra Korolova, David Kempe et al.
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
Jiaqi Zhai, Yunxing Liao, Xing Liu et al.
GiLOT: Interpreting Generative Language Models via Optimal Transport
Xuhong Li, Jiamin Chen, Yekun Chai et al.
Transitional Uncertainty with Layered Intermediate Predictions
Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib
Prompt Sketching for Large Language Models
Luca Beurer-Kellner, Mark Müller, Marc Fischer et al.
Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models
Hengyi Wang, Shiwei Tan, Hao Wang
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
Zhenlong Liu, Lei Feng, HUIPING ZHUANG et al.
Diversified Batch Selection for Training Acceleration
Feng Hong, Yueming LYU, Jiangchao Yao et al.
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
Jiarong Pan, Stefan Falkner, Felix Berkenkamp et al.
A Geometric Decomposition of Finite Games: Convergence vs. Recurrence under Exponential Weights
Davide Legacci, Panayotis Mertikopoulos, Bary Pradelski
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits
Jiachen Wang, Tianji Yang, James Zou et al.
Scaling Laws for the Value of Individual Data Points in Machine Learning
Ian Covert, Wenlong Ji, Tatsunori Hashimoto et al.
Learning and Forgetting Unsafe Examples in Large Language Models
Jiachen Zhao, Zhun Deng, David Madras et al.
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing et al.
Prospector Heads: Generalized Feature Attribution for Large Models & Data
Gautam Machiraju, Alexander Derry, Arjun Desai et al.
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis
Federico Bianchi, Patrick John Chia, Mert Yuksekgonul et al.
Selecting Large Language Model to Fine-tune via Rectified Scaling Law
Haowei Lin, Baizhou Huang, Haotian Ye et al.
PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels
Praneeth Kacham, Vahab Mirrokni, Peilin Zhong
Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation
Lujie Yang, Hongkai Dai, Zhouxing Shi et al.
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
Zhening Li, Gabriel Poesia, Armando Solar-Lezama
Assessing Large Language Models on Climate Information
Jannis Bulian, Mike Schäfer, Afra Amini et al.
The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning
Nathaniel Li, Alexander Pan, Anjali Gopal et al.
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Zhifeng Kong, ARUSHI GOEL, Rohan Badlani et al.
An Explicit Frame Construction for Normalizing 3D Point Clouds
Justin Baker, Shih-Hsin Wang, Tommaso de Fernex et al.
Align Your Steps: Optimizing Sampling Schedules in Diffusion Models
Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis
Distributional Bellman Operators over Mean Embeddings
Li Kevin Wenliang, Gregoire Deletang, Matthew Aitchison et al.
Comparing Graph Transformers via Positional Encodings
Mitchell Black, Zhengchao Wan, Gal Mishne et al.
ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections
Massimo Bini, Karsten Roth, Zeynep Akata et al.
DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving
Foteini Strati, Sara McAllister, Amar Phanishayee et al.
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses
Changyu Gao, Andrew Lowy, Xingyu Zhou et al.
Incremental Topological Ordering and Cycle Detection with Predictions
Samuel McCauley, Benjamin Moseley, Aidin Niaparast et al.
Reweighted Solutions for Weighted Low Rank Approximation
David Woodruff, Taisuke Yasuda
Coresets for Multiple $\ell_p$ Regression
David Woodruff, Taisuke Yasuda
Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching
Rico Angell, Andrew McCallum
Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data
Kishan Panaganti, Adam Wierman, Eric Mazumdar
A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM)
Dehao Yuan, Cornelia Fermuller, Tahseen Rabbani et al.
WAVES: Benchmarking the Robustness of Image Watermarks
Bang An, Mucong Ding, Tahseen Rabbani et al.
How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective
Keyan Miao, Konstantinos Gatsis
GPT-4V(ision) is a Generalist Web Agent, if Grounded
Boyuan Zheng, Boyu Gou, Jihyung Kil et al.
LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models
Tianci Liu, Haoyu Wang, Shiyang Wang et al.
Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
Alan Amin, Andrew Wilson
Continuous Treatment Effects with Surrogate Outcomes
Zhenghao Zeng, David Arbour, Avi Feller et al.
Editing Partially Observable Networks via Graph Diffusion Models
Puja Trivedi, Ryan A Rossi, David Arbour et al.
Meta Evidential Transformer for Few-Shot Open-Set Recognition
Hitesh Sapkota, Krishna Neupane, Qi Yu
Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity
Hagyeong Lee, Minkyu Kim, Jun-Hyuk Kim et al.
NExT-Chat: An LMM for Chat, Detection and Segmentation
Ao Zhang, Yuan Yao, Wei Ji et al.
CKGConv: General Graph Convolution with Continuous Kernels
Liheng Ma, Soumyasundar Pal, Yitian Zhang et al.
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
Mo Yu, Qiujing Wang, Shunchi Zhang et al.
Position: Social Environment Design Should be Further Developed for AI-based Policy-Making
Edwin Zhang, Sadie Zhao, Tonghan Wang et al.
CaPS: Collaborative and Private Synthetic Data Generation from Distributed Sources
Sikha Pentyala, Mayana Pereira, Martine De Cock
${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
Dingyang Chen, Qi Zhang
Grokking Group Multiplication with Cosets
Dashiell Stander, Qinan Yu, Honglu Fan et al.
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews
Weixin Liang, Zachary Izzo, Yaohui Zhang et al.
Cell2Sentence: Teaching Large Language Models the Language of Biology
Daniel Levine, Syed Rizvi, Sacha Lévy et al.
The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks
Songhua He, Periklis Papakonstantinou
Augmenting Decision with Hypothesis in Reinforcement Learning
Nguyen Minh Quang, Hady Lauw
Outlier-Efficient Hopfield Layers for Large Transformer-Based Models
Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Haozheng Luo et al.