Most Cited ICML "3d shape reconstruction" Papers
5,975 papers found • Page 15 of 30
Conference
Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
Zeyuan Allen-Zhu, Yuanzhi Li
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui et al.
The Privacy Power of Correlated Noise in Decentralized Learning
Youssef Allouah, Anastasiia Koloskova, Aymane Firdoussi et al.
Robust and Conjugate Gaussian Process Regression
Matias Altamirano, Francois-Xavier Briol, Jeremias Knoblauch
Position: Stop Making Unscientific AGI Performance Claims
Patrick Altmeyer, Andrew Demetriou, Antony Bartlett et al.
Hyperbolic Optimizer as a Dynamical System
Nico Alvarado, Hans Lobel
Stationarity without mean reversion in improper Gaussian processes
Luca Ambrogioni
Robust Graph Matching when Nodes are Corrupt
Taha Ameen Ur Rahman, Bruce Hajek
Fast Algorithms for Hypergraph PageRank with Applications to Semi-Supervised Learning
Konstantinos Ameranis, Adela DePavia, Lorenzo Orecchia et al.
Scalable Online Exploration via Coverability
Philip Amortila, Dylan Foster, Akshay Krishnamurthy
Adaptive Hierarchical Certification for Segmentation using Randomized Smoothing
Alaa Anani, Tobias Lorenz, Bernt Schiele et al.
Online conformal prediction with decaying step sizes
Anastasios Angelopoulos, Rina Barber, Stephen Bates
A Rate-Distortion View of Uncertainty Quantification
Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen et al.
Practical Performance Guarantees for Pipelined DNN Inference
Aaron Archer, Matthew Fahrbach, Kuikui Liu et al.
Causal Action Influence Aware Counterfactual Data Augmentation
Núria Armengol Urpí, Marco Bagatella, Marin Vlastelica et al.
An amortized approach to non-linear mixed-effects modeling based on neural posterior estimation
Jonas Arruda, Yannik Schälte, Clemens Peiter et al.
Learning the Target Network in Function Space
Kavosh Asadi, Yao Liu, Shoham Sabach et al.
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
Hilal Asi, Vitaly Feldman, Jelani Nelson et al.
Delaunay Graph: Addressing Over-Squashing and Over-Smoothing Using Delaunay Triangulation
Hugo Attali, Davide Buscaldi, Nathalie Pernelle
How Free is Parameter-Free Stochastic Optimization?
Amit Attia, Tomer Koren
Random features models: a way to study the success of naive imputation
Alexis Ayme, Claire Boyer, Aymeric Dieuleveut et al.
Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS
Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani
Simulation of Graph Algorithms with Looped Transformers
Artur Back de Luca, Kimon Fountoulakis
Diffusion Models Demand Contrastive Guidance for Adversarial Purification to Advance
Mingyuan Bai, Wei Huang, Li Tenghui et al.
On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
Yunyan Bai, Yuxing Liu, Luo Luo
Constrained Ensemble Exploration for Unsupervised Skill Discovery
Chenjia Bai, Rushuai Yang, Qiaosheng Zhang et al.
Memory Consolidation Enables Long-Context Video Understanding
Ivana Balazevic, Yuge Shi, Pinelopi Papalampidi et al.
On the Identifiability of Switching Dynamical Systems
Carles Balsells-Rodas, Yixin Wang, Yingzhen Li
Analyzing $D^\alpha$ seeding for $k$-means
Etienne Bamas, Sai Ganesh Nagarajan, Ola Svensson
Relational DNN Verification With Cross Executional Bound Refinement
Debangshu Banerjee, Gagandeep Singh
VNN: Verification-Friendly Neural Networks with Hard Robustness Guarantees
Anahita Baninajjar, Ahmed Rezine, Amir Aminifar
Scale-Free Image Keypoints Using Differentiable Persistent Homology
Giovanni Barbarani, Francesco Vaccarino, Gabriele Trivigno et al.
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies
Brian Bartoldson, James Diffenderfer, Konstantinos Parasyris et al.
Neural Diffusion Models
Grigory Bartosh, Dmitry Vetrov, Christian Andersson Naesseth
Generalization in Kernel Regression Under Realistic Assumptions
Daniel Barzilai, Ohad Shamir
On Mechanistic Knowledge Localization in Text-to-Image Generative Models
Samyadeep Basu, Keivan Rezaei, Priyatham Kattakinda et al.
Monotone Individual Fairness
Yahav Bechavod
Vocabulary for Universal Approximation: A Linguistic Perspective of Mapping Compositions
Yongqiang Cai
Standardized Interpretable Fairness Measures for Continuous Risk Scores
Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann
Neural Networks Learn Statistics of Increasing Complexity
Nora Belrose, Quintin Pope, Lucia Quirke et al.
The Role of Learning Algorithms in Collective Action
Omri Ben-Dov, Jake Fawkes, Samira Samadi et al.
CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
Jules Berman, Benjamin Peherstorfer
By Tying Embeddings You Are Assuming the Distributional Hypothesis
Bertolotti Francesco, Walter Cazzola
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok
Refining Minimax Regret for Unsupervised Environment Design
Michael Beukman, Samuel Coward, Michael Matthews et al.
Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation
Luca Beurer-Kellner, Marc Fischer, Martin Vechev
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
Aleksandr Beznosikov, David Dobre, Gauthier Gidel
Position: Scaling Simulation is Neither Necessary Nor Sufficient for In-the-Wild Robot Manipulation
Homanga Bharadhwaj
Why do Variational Autoencoders Really Promote Disentanglement?
Pratik Bhowal, Achint Soni, Sirisha Rambhatla
Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman
Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning
Yuxuan Bian, Xuan Ju, Jiangtong Li et al.
Naive Bayes Classifiers over Missing Data: Decision and Poisoning
Song Bian, Xiating Ouyang, ZHIWEI FAN et al.
Improving fine-grained understanding in image-text pre-training
Ioana Bica, Anastasija Ilic, Matthias Bauer et al.
Position: Explain to Question not to Justify
Przemyslaw Biecek, Wojciech Samek
Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering
Mitchell Black, Lucy Lin, Weng-Keen Wong et al.
Stability Evaluation through Distributional Perturbation Analysis
Jose Blanchet, Peng Cui, Jiajin Li et al.
Dynamic Survival Analysis with Controlled Latent States
Linus Bleistein, Van NGUYEN, Adeline Fermanian et al.
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
Denis Blessing, Xiaogang Jia, Johannes Esslinger et al.
Shifted Interpolation for Differential Privacy
Jinho Bok, Weijie Su, Jason Altschuler
How Spurious Features are Memorized: Precise Analysis for Random and NTK Features
Simone Bombari, Marco Mondelli
Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features
Simone Bombari, Marco Mondelli
Position: Machine Learning-powered Assessments of the EU Digital Services Act Aid Quantify Policy Impacts on Online Harms
Eleonora Bonel, Luca Nannini, Davide Bassi et al.
Random matrix theory improved Fréchet mean of symmetric positive definite matrices
Florent Bouchard, Ammar Mian, Malik TIOMOKO et al.
On dimensionality of feature vectors in MPNNs
César Bravo, Alexander Kozachinskiy, Cristobal Rojas
Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees
Marco Bressan, Mauro Sozio
Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu's formula
Kirill Brilliantov, Fedor Pavutnitskiy, Dmitrii A. Pasechniuk et al.
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation
Gavin Brown, Krishnamurthy Dvijotham, Georgina Evans et al.
Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples
Dake Bu, Wei Huang, Taiji Suzuki et al.
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee et al.
Differentially Private Bias-Term Fine-tuning of Foundation Models
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha et al.
Langevin Policy for Safe Reinforcement Learning
Fenghao Lei, Long Yang, Shiting Wen et al.
Semantically-correlated memories in a dense associative model
Thomas F Burns
How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
Gon Buzaglo, Itamar Harel, Mor Shpigel Nacson et al.
Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads
Tianle Cai, Yuhong Li, Zhengyang Geng et al.
Enhancing Cross-Modal Fine-Tuning with Gradually Intermediate Modality Generation
Lincan Cai, Shuang Li, Wenxuan Ma et al.
Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion
Yang Cai, Argyris Oikonomou, Weiqiang Zheng
Sample-specific Masks for Visual Reprogramming-based Prompting
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design
Andrew Campbell, Jason Yim, Regina Barzilay et al.
Successor Features for Efficient Multi-Subject Controlled Text Generation
Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung et al.
Limited Preference Aided Imitation Learning from Imperfect Demonstrations
Xingchen Cao, Fan-Ming Luo, Junyin Ye et al.
Predictive Dynamic Fusion
Bing Cao, Yinan Xia, Yi Ding et al.
Can a Few Decide for Many? The Metric Distortion of Sortition
Ioannis Caragiannis, Evi Micha, Jannik Peters
AI Alignment with Changing and Influenceable Reward Functions
Micah Carroll, Davis Foote, Anand Siththaranjan et al.
Online Learning under Budget and ROI Constraints via Weak Adaptivity
Matteo Castiglioni, Andrea Celli, Christian Kroer
On the Implicit Bias of Adam
Matias Cattaneo, Jason Klusowski, Boris Shigida
Feasibility Consistent Representation Learning for Safe Reinforcement Learning
Zhepeng Cen, Yihang Yao, Zuxin Liu et al.
Simple Ingredients for Offline Reinforcement Learning
Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta et al.
Auditing Private Prediction
Karan Chadha, Matthew Jagielski, Nicolas Papernot et al.
Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation
Guiyang Chan, Pengcheng Zhang, Hai Dong et al.
Feature Importance Disparities for Data Bias Investigations
Peter Chang, Leor Fishman, Seth Neel
Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
Serina Chang, Frederic Koehler, Zhaonan Qu et al.
MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion
Di Chang, Yichun Shi, Quankai Gao et al.
How Interpretable Are Interpretable Graph Neural Networks?
Yongqiang Chen, Yatao Bian, Bo Han et al.
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning
Weilin Chen, Ruichu Cai, Zeqin Yang et al.
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
Xuexin Chen, Ruichu Cai, Zhengting Huang et al.
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models
Lichang Chen, Jiuhai Chen, Tom Goldstein et al.
MaSS: Multi-attribute Selective Suppression for Utility-preserving Data Transformation from an Information-theoretic Perspective
Yizhuo Chen, Chun-Fu (Richard) Chen, Hsiang Hsu et al.
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Zixiang Chen, Yihe Deng, Huizhuo Yuan et al.
Robust Classification via a Single Diffusion Model
Huanran Chen, Yinpeng Dong, Zhengyi Wang et al.
Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective
Yang Chen, Cong Fang, Zhouchen Lin et al.
Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components
Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low
RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content
Zhuowen Yuan, Zidi Xiong, Yi Zeng et al.
Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes
Yifan Chen, Mark Goldstein, Mengjian Hua et al.
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding
Kaiyuan Chen, Xingzhuo Guo, Yu Zhang et al.
Bagged Deep Image Prior for Recovering Images in the Presence of Speckle Noise
Xi Chen, Zhewen Hou, Christopher Metzler et al.
Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces
Ziyi Chen, Heng Huang
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
Wei-Ning Chen, Berivan Isik, Peter Kairouz et al.
Offline Transition Modeling via Contrastive Energy Learning
Ruifeng Chen, Chengxing Jia, Zefang Huang et al.
Efficient Pareto Manifold Learning with Low-Rank Structure
Weiyu CHEN, James Kwok
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
Mouxiang Chen, Chenghao Liu, Zemin Liu et al.
High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
Yihang Chen, Fanghui Liu, Taiji Suzuki et al.
DiJiang: Efficient Large Language Models through Compact Kernelization
Hanting Chen, Liuzhicheng Liuzhicheng, Xutao Wang et al.
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism
Yanxi Chen, Xuchen Pan, Yaliang Li et al.
MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
Justin Chih-Yao Chen, Swarnadeep Saha, Elias Stengel-Eskin et al.
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process
Guangyi Chen, Yifan Shen, Zhenhao Chen et al.
GRATH: Gradual Self-Truthifying for Large Language Models
Weixin Chen, Dawn Song, Bo Li
Performative Prediction with Bandit Feedback: Learning through Reparameterization
Yatong Chen, Wei Tang, Chien-Ju Ho et al.
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
Yingyi Chen, Qinghua Tao, Francesco Tonin et al.
Recovering Labels from Local Updates in Federated Learning
Huancheng Chen, Haris Vikalo
Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy
Ziqin Chen, Yongqiang Wang
Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments
Runfa Chen, Ling Wang, Yu Du et al.
A General Framework for Learning from Weak Supervision
Hao Chen, Jindong Wang, Lei Feng et al.
Diffusion Model-Augmented Behavioral Cloning
Shang-Fu Chen, Hsiang-Chun Wang, Ming-Hao Hsu et al.
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
Junfeng CHEN, Kailiang Wu
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
Shiqi Chen, Miao Xiong, Junteng Liu et al.
Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting
Anthony Chen, Huanrui Yang, Yulu Gan et al.
DRCT: Diffusion Reconstruction Contrastive Training towards Universal Detection of Diffusion Generated Images
Baoying Chen, Jishen Zeng, Jianquan Yang et al.
FedMBridge: Bridgeable Multimodal Federated Learning
Jiayi Chen, Aidong Zhang
Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness
Honghao Chen, Zhang Yurong, xiaokun Feng et al.
Diffusive Gibbs Sampling
Wenlin Chen, Mingtian Zhang, Brooks Paige et al.
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
Yu Chen, XiangCheng Zhang, Siwei Wang et al.
LLaGA: Large Language and Graph Assistant
Runjin Chen, Tong Zhao, Ajay Jaiswal et al.
Compact Optimality Verification for Optimization Proxies
Wenbo Chen, Haoruo Zhao, Mathieu Tanneau et al.
Enhancing Implicit Shape Generators Using Topological Regularizations
Liyan Chen, Yan Zheng, Yang Li et al.
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.
RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation
Zelei Cheng, Xian Wu, Jiahao Yu et al.
RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences
Jie Cheng, Gang Xiong, Xingyuan Dai 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
Leveraging (Biased) Information: Multi-armed Bandits with Offline Data
Wang Chi Cheung, Lixing Lyu
Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning
Chia-Cheng Chiang, Li-Cheng Lan, Wei-Fang Sun et al.
MS-TIP: Imputation Aware Pedestrian Trajectory Prediction
Pranav Singh Chib, Achintya Nath, Paritosh Kabra et al.
Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
Pranav Singh Chib, Pravendra Singh
How Flawed Is ECE? An Analysis via Logit Smoothing
Muthu Chidambaram, Holden Lee, Colin McSwiggen 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
Neurodegenerative Brain Network Classification via Adaptive Diffusion with Temporal Regularization
Hyuna Cho, Jaeyoon Sim, Guorong Wu et al.
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.
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
Hyeong Kyu Choi, Sharon Li
Online bipartite matching with imperfect advice
Davin Choo, Themis Gouleakis, Chun Kai Ling 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.
Prompt-tuning Latent Diffusion Models for Inverse Problems
Hyungjin Chung, Jong Chul YE, Peyman Milanfar et al.
Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens
Ross Clarke, Jose Miguel Hernandez-Lobato
$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
Pierre Clavier, Tom Huix, Alain Oliviero Durmus
Improving Token-Based World Models with Parallel Observation Prediction
Lior Cohen, Kaixin Wang, Bingyi Kang et al.
Multi-View Stochastic Block Models
Vincent Cohen-Addad, Tommaso d'Orsi, Silvio Lattanzi et al.
Weighted distance nearest neighbor condensing
Lee-Ad Gottlieb, Timor Sharabi, Roi Weiss
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.
A2Q+: Improving Accumulator-Aware Weight Quantization
Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig et al.
Statistical Inference Under Constrained Selection Bias
Santiago Cortes-Gomez, Mateo Dulce Rubio, Carlos Miguel Patiño et al.
Conformal Prediction Sets Improve Human Decision Making
Jesse Cresswell, yi sui, Bhargava Kumar et al.
Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity Analysis
Daniel Csillag, Claudio Struchiner, Guilherme Goedert
Harmonizing Generalization and Personalization in Federated Prompt Learning
Tianyu Cui, Hongxia Li, Jingya Wang et al.
ULTRAFEEDBACK: Boosting Language Models with Scaled AI Feedback
Ganqu Cui, Lifan Yuan, Ning Ding 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.
Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation
Juntao Dai, Yaodong Yang, Qian Zheng et al.
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model
Hien Dang, Tho Tran Huu, Tan Nguyen 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.
New Bounds on the Cohesion of Complete-link and Other Linkage Methods for Agglomerative Clustering
Sanjoy Dasgupta, Eduardo Laber
Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction
Riccardo De Santi, Federico Arangath Joseph, Noah Liniger et al.
Global Reinforcement Learning : Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods
Riccardo De Santi, Manish Prajapat, Andreas Krause
Provably Better Explanations with Optimized Aggregation of Feature Attributions
Thomas Decker, Ananta Bhattarai, Jindong Gu et al.
Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments
Antoine Dedieu, Wolfgang Lehrach, Guangyao Zhou et al.
Asymptotically Optimal and Computationally Efficient Average Treatment Effect Estimation in A/B testing
VIKAS DEEP, Achal Bassamboo, Sandeep Juneja
Predicting Lagrangian Multipliers for Mixed Integer Linear Programs
Francesco Demelas, Joseph Roux, Mathieu Lacroix et al.
Prediction-powered Generalization of Causal Inferences
Ilker Demirel, Ahmed Alaa, Anthony Philippakis et al.
An Unsupervised Approach for Periodic Source Detection in Time Series
Berken Utku Demirel, Christian Holz
Collaborative Learning with Different Labeling Functions
yuyang deng, Mingda Qiao
Exploring the Low-Pass Filtering Behavior in Image Super-Resolution
Haoyu Deng, Zijing Xu, Yule Duan et al.
Network Tight Community Detection
Jiayi Deng, Xiaodong Yang, Jun Yu et al.
Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos et al.
Multicalibration for Confidence Scoring in LLMs
Gianluca Detommaso, Martin A Bertran, Riccardo Fogliato et al.
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning
Jannik Deuschel, Caleb Ellington, Yingtao Luo et al.
Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies
Alex DeWeese, Guannan Qu
Trust Regions for Explanations via Black-Box Probabilistic Certification
Amit Dhurandhar, Swagatam Haldar, Dennis Wei et al.
Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods
Hao Di, Haishan Ye, Xiangyu Chang et al.
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient
Hao Di, Haishan Ye, Yueling Zhang et al.
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.