Most Cited 2024 "3d feature learning" Papers
12,324 papers found • Page 59 of 62
Conference
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.
Prompt-tuning Latent Diffusion Models for Inverse Problems
Hyungjin Chung, Jong Chul YE, Peyman Milanfar et al.
$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
Pierre Clavier, Tom Huix, Alain Oliviero Durmus
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
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.
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.
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.
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.
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
Prediction-powered Generalization of Causal Inferences
Ilker Demirel, Ahmed Alaa, Anthony Philippakis et al.
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.
Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos et al.
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning
Jannik Deuschel, Caleb Ellington, Yingtao Luo et al.
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.
Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning
Charles Dickens, Changyu Gao, Connor Pryor et al.
Efficient Algorithms for Sum-Of-Minimum Optimization
Lisang Ding, Ziang Chen, Xinshang Wang et al.
Robust Stable Spiking Neural Networks
Ding Jianhao, Zhiyu Pan, Yujia Liu et al.
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Yiran Ding, Li Lyna Zhang, Chengruidong Zhang et al.
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
Daniel Dodd, Louis Sharrock, Chris Nemeth
Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
Nikita Doikov, Sebastian Stich, Martin Jaggi
Accelerating PDE Data Generation via Differential Operator Action in Solution Space
huanshuo dong, Hong Wang, Haoyang Liu et al.
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference
Harry Dong, Xinyu Yang, Zhenyu Zhang et al.
Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent
Konstantin Donhauser, Javier Abad, Neha Hulkund et al.
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows
Felix Draxler, Stefan Wahl, Christoph Schnörr et al.
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
YU DU, Fangyun Wei, Hongyang Zhang
MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving
Jiangfei Duan, Runyu Lu, Haojie Duanmu et al.
DE-COP: Detecting Copyrighted Content in Language Models Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
Sharpness-Aware Data Generation for Zero-shot Quantization
Hoang Dung, Cuong Pham, Trung Le et al.
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
Max Dupre la Tour, Monika Henzinger, David Saulpic
Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation
Benjamin Dupuis, Umut Simsekli
Outlier-robust Kalman Filtering through Generalised Bayes
Gerardo Duran-Martin, Matias Altamirano, Alex Shestopaloff et al.
Position: Insights from Survey Methodology can Improve Training Data
Stephanie Eckman, Barbara Plank, Frauke Kreuter
Approximate Nearest Neighbor Search with Window Filters
Josh Engels, Ben Landrum, Shangdi Yu et al.
DsDm: Model-Aware Dataset Selection with Datamodels
Logan Engstrom
Compositional Curvature Bounds for Deep Neural Networks
Taha Entesari, Sina Sharifi, Mahyar Fazlyab
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
Benjamin Eyre, Elliot Creager, David Madras et al.
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
Han Fang, Zhihao Song, Paul Weng et al.
Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition
Hao Fei, Shengqiong Wu, Wei Ji et al.
Fast White-Box Adversarial Streaming Without a Random Oracle
Ying Feng, Aayush Jain, David Woodruff
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao et al.
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs
Kaituo Feng, Changsheng Li, Xiaolu Zhang et al.
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates
Rémi Leluc, Aymeric Dieuleveut, François Portier et al.
Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
Thomas Ferté, Dutartre Dan, Boris Hejblum et al.
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
Matthias Fey, Weihua Hu, Kexin Huang et al.
Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields
Tom Fischer, Pascal Peter, Joachim Weickert et al.
Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
Aaron Fisher
Interpretability Illusions in the Generalization of Simplified Models
Dan Friedman, Andrew Lampinen, Lucas Dixon et al.
Hyperbolic Geometric Latent Diffusion Model for Graph Generation
Xingcheng Fu, Yisen Gao, Yuecen Wei et al.
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin et al.
PinNet: Pinpoint Instructive Information for Retrieval Augmented Code-to-Text Generation
Han Fu, Jian Tan, Pinhan Zhang et al.
Towards Theoretical Understandings of Self-Consuming Generative Models
Shi Fu, Sen Zhang, Yingjie Wang et al.
Positive Concave Deep Equilibrium Models
Mateusz Gabor, Tomasz Piotrowski, Renato L. G. Cavalcante
Let Go of Your Labels with Unsupervised Transfer
Artyom Gadetsky, Yulun Jiang, Maria Brbic
Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
Kai Gan, Tong Wei
Reflective Policy Optimization
Yaozhong Gan, yan renye, zhe wu et al.
Testing the Feasibility of Linear Programs with Bandit Feedback
Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama et al.
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
Hongchang Gao
A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
Zhangyang Gao, Daize Dong, Cheng Tan et al.
Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
Riqiang Gao, Florin-Cristian Ghesu, Simon Arberet et al.
DMTG: One-Shot Differentiable Multi-Task Grouping
Yuan Gao, Shuguo Jiang, Moran Li et al.
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion
Bowen Gao, Minsi Ren, Yuyan Ni et al.
Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations
Feng Gao, Liangzhi Shi, Shenao Zhang et al.
Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
Wenzhi Gao, Chunlin Sun, Chenyu Xue et al.
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
Chenyin Gao, ZHIMING ZHANG, Shu Yang
Projection-Free Online Convex Optimization with Time-Varying Constraints
Dan Garber, Ben Kretzu
LLark: A Multimodal Instruction-Following Language Model for Music
Josh Gardner, Simon Durand, Daniel Stoller et al.
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
Bruno Gavranović, Paul Lessard, Andrew Dudzik et al.
Safe and Robust Subgame Exploitation in Imperfect Information Games
Zhenxing Ge, Zheng Xu, Tianyu Ding et al.
Learning with 3D rotations, a hitchhiker's guide to SO(3)
Andreas René Geist, Jonas Frey, Mikel Zhobro et al.
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar et al.
State-Constrained Zero-Sum Differential Games with One-Sided Information
Mukesh Ghimire, Lei Zhang, Zhe Xu et al.
Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms
Avishek Ghosh, Arya Mazumdar
Self-Correcting Self-Consuming Loops for Generative Model Training
Nate Gillman, Michael Freeman, Daksh Aggarwal et al.
Evolution-Inspired Loss Functions for Protein Representation Learning
Chengyue Gong, Adam Klivans, James Loy et al.
Long Range Propagation on Continuous-Time Dynamic Graphs
Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio et al.
AI Control: Improving Safety Despite Intentional Subversion
Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan et al.
Predictive Performance Comparison of Decision Policies Under Confounding
Luke Guerdan, Amanda Coston, Ken Holstein et al.
ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation
Ziao Guo, Yang Li, Chang Liu et al.
Compressing Large Language Models by Joint Sparsification and Quantization
Jinyang Guo, Jianyu Wu, Zining Wang et al.
Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
Zijian Guo, Weichao Zhou, Wenchao Li
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
Jan Hagnberger, Marimuthu Kalimuthu, Daniel Musekamp et al.
Prototypical Transformer As Unified Motion Learners
Cheng Han, Yawen Lu, Guohao Sun et al.
MGit: A Model Versioning and Management System
Wei Hao, Daniel Mendoza, Rafael Mendes et al.
Estimating the Permanent by Nesting Importance Sampling
Juha Harviainen, Mikko Koivisto
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer
Doron Haviv, Russell Kunes, Thomas Dougherty et al.
GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements
Alexander Havrilla, Sharath Chandra Raparthy, Christoforos Nalmpantis et al.
Deep Neural Room Acoustics Primitive
Yuhang He, Anoop Cherian, Gordon Wichern et al.
ReDiffuser: Reliable Decision-Making Using a Diffuser with Confidence Estimation
Nantian He, Shaohui Li, Zhi Li et al.
Quantum Algorithm for Online Exp-concave Optimization
Jianhao He, Chengchang Liu, Xutong Liu et al.
Riemannian Accelerated Zeroth-order Algorithm: Improved Robustness and Lower Query Complexity
Chang He, Zhaoye Pan, Xiao Wang et al.
Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning
Zhiyuan He, Yijun Yang, Pin-Yu Chen et al.
Robust Multi-Task Learning with Excess Risks
Yifei He, Shiji Zhou, Guojun Zhang et al.
DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
Kaibo He, Chenhui Zuo, Chengtian Ma et al.
Learning Useful Representations of Recurrent Neural Network Weight Matrices
Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber
Randomized Confidence Bounds for Stochastic Partial Monitoring
Maxime Heuillet, Ola Ahmad, Audrey Durand
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
Minh Hoang, Azza Fadhel, Aryan Deshwal et al.
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
Junyuan Hong, Jinhao Duan, Chenhui Zhang et al.
Enhancing Sufficient Dimension Reduction via Hellinger Correlation
Seungbeom Hong, Ilmun Kim, Jun Song
A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs
Kihyuk Hong, Ambuj Tewari
Equilibrium of Data Markets with Externality
Safwan Hossain, Yiling Chen
IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency
Linshan Hou, Ruili Feng, Zhongyun Hua et al.
Loss Shaping Constraints for Long-Term Time Series Forecasting
Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro
Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning
Yusong Hu, De Cheng, Dingwen Zhang et al.
An Information Theoretic Approach to Interaction-Grounded Learning
Xiaoyan Hu, Farzan Farnia, Ho-fung Leung
Provable Privacy with Non-Private Pre-Processing
Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf
Case-Based or Rule-Based: How Do Transformers Do the Math?
Yi Hu, Xiaojuan Tang, Haotong Yang et al.
Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications
Zixuan Hu, Yongxian Wei, Li Shen et al.
ReconBoost: Boosting Can Achieve Modality Reconcilement
Cong Hua, Qianqian Xu, Shilong Bao et al.
Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games
Kexin Huang, Ziqian Chen, xue wang et al.
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
Jiawei Huang, Niao He, Andreas Krause
CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Yulong Huang, Xiaopeng LIN, Hongwei Ren et al.
MFTN: A Multi-scale Feature Transfer Network Based on IMatchFormer for Hyperspectral Image Super-Resolution
Shuying Huang, Mingyang Ren, Yong Yang et al.
Quasi-Monte Carlo Features for Kernel Approximation
ZHEN HUANG, Jiajin Sun, Yian Huang
Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation
Zhilin Huang, Ling Yang, Xiangxin Zhou et al.
Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence
Yancheng Huang, Kai Yang, Zelin Zhu et al.
An Embodied Generalist Agent in 3D World
Jiangyong Huang, Silong Yong, Xiaojian Ma et al.
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning
Joon Suk Huh, Kirthevasan Kandasamy
Make-A-Shape: a Ten-Million-scale 3D Shape Model
Ka-Hei Hui, Aditya Sanghi, Arianna Rampini et al.
Vanilla Bayesian Optimization Performs Great in High Dimensions
Carl Hvarfner, Erik Hellsten, Luigi Nardi
Smooth Min-Max Monotonic Networks
Christian Igel
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov et al.
Understanding the Learning Dynamics of Alignment with Human Feedback
Shawn Im, Sharon Li
Zero-Shot Reinforcement Learning via Function Encoders
Tyler Ingebrand, Amy Zhang, Ufuk Topcu
Online Non-stochastic Control with Partial Feedback
Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou
Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD
Jonggyu Jang, Seongjin Hwang, Hyun Jong Yang
Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method
Jeeveswaran Kishaan, Elahe Arani, Bahram Zonooz
Finite Volume Features, Global Geometry Representations, and Residual Training for Deep Learning-based CFD Simulation
Loh S.E. Jessica, Naheed Anjum Arafat, Wei Xian Lim et al.
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages
Andrew Jesson, Christopher Lu, Gunshi Gupta et al.
ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization
Tianying Ji, Yongyuan Liang, Yan Zeng et al.
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer
Ding Jia, Jianyuan Guo, Kai Han et al.
Generalized Neural Collapse for a Large Number of Classes
Jiachen Jiang, Jinxin Zhou, Peng Wang et al.
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning
Shibo Jie, Yehui Tang, Ning Ding et al.
Homomorphism Counts for Graph Neural Networks: All About That Basis
Emily Jin, Michael Bronstein, Ismail Ceylan et al.
Language Models as Semantic Indexers
Bowen Jin, Hansi Zeng, Guoyin Wang et al.
Position: What Can Large Language Models Tell Us about Time Series Analysis
Ming Jin, Yi-Fan Zhang, Wei Chen et al.
Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks
Mikkel Jordahn, Pablo Olmos
Position: Benchmarking is Limited in Reinforcement Learning Research
Scott Jordan, Adam White, Bruno da Silva et al.
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?
Mira Juergens, Nis Meinert, Viktor Bengs et al.
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
Georgios Kaissis, Stefan Kolek, Borja de Balle Pigem et al.
C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models
Mintong Kang, Nezihe Merve Gürel, Ning Yu et al.
Think Before You Act: Decision Transformers with Working Memory
Jikun Kang, Romain Laroche, Xingdi Yuan et al.
Certifiably Byzantine-Robust Federated Conformal Prediction
Mintong Kang, Zhen Lin, Jimeng Sun et al.
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery
Amir Mohammad Karimi Mamaghan, Panagiotis Tigas, Karl Johansson et al.
Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choice
Masahiro Kato, Oga Akihiro, Wataru Komatsubara et al.
Pluvial Flood Emulation with Hydraulics-informed Message Passing
Arnold Kazadi, James Doss-Gollin, Arlei Silva
Accelerating Convergence in Bayesian Few-Shot Classification
Tianjun Ke, Haoqun Cao, Feng Zhou
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
Zhifa Ke, Zaiwen Wen, Junyu Zhang
Fair Classification with Partial Feedback: An Exploration-Based Data Collection Approach
Vijay Keswani, Anay Mehrotra, L. Elisa Celis
Breaking through the learning plateaus of in-context learning in Transformer
Jingwen Fu, Tao Yang, Yuwang Wang et al.
Tuning-Free Stochastic Optimization
Ahmed Khaled, Chi Jin
Off-policy Evaluation Beyond Overlap: Sharp Partial Identification Under Smoothness
Samir Khan, Martin Saveski, Johan Ugander
Gaussian Plane-Wave Neural Operator for Electron Density Estimation
Seongsu Kim, Sungsoo Ahn
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning
Do-Yeon Kim, Dong-Jun Han, Jun Seo et al.
Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization
Nayeong Kim, Juwon Kang, Sungsoo Ahn et al.
Clustered Federated Learning via Gradient-based Partitioning
Heasung Kim, Hyeji Kim, Gustavo De Veciana
Demystifying SGD with Doubly Stochastic Gradients
Kyurae Kim, Joohwan Ko, Yian Ma et al.
Risk-Sensitive Policy Optimization via Predictive CVaR Policy Gradient
Ju-Hyun Kim, Seungki Min
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
Sungyoon Kim, Mert Pilanci
Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape
Juno Kim, Taiji Suzuki
An Infinite-Width Analysis on the Jacobian-Regularised Training of a Neural Network
Taeyoung Kim, Hongseok Yang
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning
Doyoung Kim, Susik Yoon, Dongmin Park et al.
A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback
Kihyun Kim, Jiawei Zhang, Asuman Ozdaglar et al.
Provably Scalable Black-Box Variational Inference with Structured Variational Families
Joohwan Ko, Kyurae Kim, Woo Chang Kim et al.
Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis
Juyeon Ko, Inho Kong, Dogyun Park et al.
Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth
Kevin Kögler, Aleksandr Shevchenko, Hamed Hassani et al.
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion
Adeesh Kolluru, John Kitchin
On Convergence of Incremental Gradient for Non-convex Smooth Functions
Anastasiia Koloskova, Nikita Doikov, Sebastian Stich et al.
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning
Xiangzhe Kong, Wenbing Huang, Yang Liu
convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data
Roman Koshkin, Tomoki Fukai
A General Online Algorithm for Optimizing Complex Performance Metrics
Wojciech Kotlowski, Marek Wydmuch, Erik Schultheis et al.
CLLMs: Consistency Large Language Models
Siqi Kou, Lanxiang Hu, Zhezhi He et al.
PcLast: Discovering Plannable Continuous Latent States
ANURAG KOUL, Shivakanth Sujit, Shaoru Chen et al.
Sobolev Space Regularised Pre Density Models
Mark Kozdoba, Binyamin Perets, Shie Mannor
Geometry-Aware Instrumental Variable Regression
Heiner Kremer, Bernhard Schölkopf
Mean Estimation in the Add-Remove Model of Differential Privacy
Alex Kulesza, Ananda Suresh, Yuyan Wang
Collective Certified Robustness against Graph Injection Attacks
Yuni Lai, Bailin PAN, kaihuang CHEN et al.
Modeling Caption Diversity in Contrastive Vision-Language Pretraining
Samuel Lavoie, Polina Kirichenko, Mark Ibrahim et al.
Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms
Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli
Knowledge Graphs Can be Learned with Just Intersection Features
Duy Le, Shaochen (Henry) Zhong, Zirui Liu et al.
Chasing Convex Functions with Long-term Constraints
Adam Lechowicz, Nicolas Christianson, Bo Sun et al.
DataFreeShield: Defending Adversarial Attacks without Training Data
Hyeyoon Lee, Kanghyun Choi, Dain Kwon et al.
Drug Discovery with Dynamic Goal-aware Fragments
Seul Lee, Seanie Lee, Kenji Kawaguchi et al.
3D Geometric Shape Assembly via Efficient Point Cloud Matching
Nahyuk Lee, Juhong Min, Junha Lee et al.
Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization
Deokjae Lee, Hyun Oh Song, Kyunghyun Cho
Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation
JoonHo Lee, Jae Oh Woo, Juree Seok et al.
Winner-takes-all learners are geometry-aware conditional density estimators
Victor Letzelter, David Perera, Cédric Rommel et al.
DetKDS: Knowledge Distillation Search for Object Detectors
Lujun Li, Yufan Bao, Peijie Dong et al.