Most Cited ICML "causal subgraphs" Papers
5,975 papers found • Page 29 of 30
Conference
Adaptive Observation Cost Control for Variational Quantum Eigensolvers
Christopher J. Anders, Kim A. Nicoli, Bingting Wu et al.
Data Poisoning Attacks against Conformal Prediction
Yangyi Li, Aobo Chen, Wei Qian et al.
Zero-Shot Generalization of GNNs over Distinct Attribute Domains
Yangyi Shen, Jincheng Zhou, Beatrice Bevilacqua et al.
Generalizable Multi-Camera 3D Object Detection from a Single Source via Fourier Cross-View Learning
Xue Zhao, Qinying Gu, Xinbing Wang et al.
Positive and Unlabeled Learning with Controlled Probability Boundary Fence
Changchun Li, Yuanchao Dai, Lei Feng et al.
Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization
Shira Vansover-Hager, Tomer Koren, Roi Livni
Hidden No More: Attacking and Defending Private Third-Party LLM Inference
Rahul Thomas, Louai Zahran, Erica Choi et al.
Evolving Minds: Logic-Informed Inference from Temporal Action Patterns
Chao Yang, Shuting Cui, Yang Yang et al.
Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection
yuxin li, Yaoxuan Feng, Bo Chen et al.
Graph Structure Extrapolation for Out-of-Distribution Generalization
Xiner Li, Shurui Gui, Youzhi Luo et al.
Value-Evolutionary-Based Reinforcement Learning
Pengyi Li, Jianye Hao, Hongyao Tang et al.
Nonconvex Theory of $M$-estimators with Decomposable Regularizers
Weiwei Liu
Conformity Score Averaging for Classification
Rui Luo, Zhixin Zhou
Channel Normalization for Time Series Channel Identification
Seunghan Lee, Taeyoung Park, Kibok Lee
FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation
Zheng Fang, Lichuan Xiang, Xu Cai et al.
A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
Baohong Li, Haoxuan Li, Anpeng Wu et al.
Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
Baohong Li, Haoxuan Li, Ruoxuan Xiong et al.
Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation
Lan Li, Xin-Chun Li, Han-Jia Ye et al.
SSHR: More Secure Generative Steganography with High-Quality Revealed Secret Images
Jiannian Wang, Yao Lu, Guangming Lu
From Complex to Atomic: Enhancing Augmented Generation via Knowledge-Aware Dual Rewriting and Reasoning
Jinyu Wang, Jingjing Fu, Rui Wang et al.
Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
Shaojie Li, Yong Liu
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once
Zhangheng Li, Shiwei Liu, Tianlong Chen et al.
Staged and Physics-Grounded Learning Framework with Hyperintensity Prior for Pre-Contrast MRI Synthesis
Dayang Wang, Srivathsa Pasumarthi Venkata, Ajit Shankaranarayanan et al.
Learning Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking
Yongxin Li, Mengyuan Liu, You Wu et al.
Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees
Tomer Meir, Uri Shalit, Malka Gorfine
DiffFPR: Diffusion Prior for Oversampled Fourier Phase Retrieval
Ji Li, Chao Wang
Adaptive Partitioning Schemes for Optimistic Optimization
Raja Sunkara, Ardhendu Tripathy
Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach
Zhihao Li, Yufei Wang, Alex Kot et al.
Reinforced Learning Explicit Circuit Representations for Quantum State Characterization from Local Measurements
Manwen Liao, Yan Zhu, Weitian Zhang et al.
$\bf{\Phi}_\textrm{Flow}$: Differentiable Simulations for PyTorch, TensorFlow and Jax
Philipp Holl, Nils Thuerey
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
Alexander Bienstock, Ujjwal Kumar, Antigoni Polychroniadou
Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias
Baohong Li, Anpeng Wu, Ruoxuan Xiong et al.
Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints
Hengquan Guo, Lingkai Zu, Xin Liu
Online Laplacian-Based Representation Learning in Reinforcement Learning
Maheed Ahmed, Jayanth Bhargav, Mahsa Ghasemi
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process
Zichong Li, Qunzhi Xu, Zhenghao Xu et al.
Statistical Properties of Robust Satisficing
zhiyi li, Yunbei Xu, Ruohan Zhan
MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training
Yang Luo, Zangwei Zheng, Ziheng Qin et al.
MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models
Jeffrey A. Chan-Santiago, praveen tirupattur, Gaurav Kumar Nayak et al.
MissScore: High-Order Score Estimation in the Presence of Missing Data
Wenqin Liu, Haoze Hou, Erdun Gao et al.
Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis
Yingying Li, Jing Yu, Lauren Conger et al.
Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference
Fabing Li, Yuanhao Zhai, Shuangyu Cai et al.
EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search
Pengyi Li, Yan Zheng, Hongyao Tang et al.
Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
Shaojie Li, Bowei Zhu, Yong Liu
Receptive Fields As Experts in Convolutional Neural Architectures
Dongze Lian, Weihao Yu, Xinchao Wang
DA-KD: Difficulty-Aware Knowledge Distillation for Efficient Large Language Models
Changyi He, Yifu Ding, Jinyang Guo et al.
ABNet: Adaptive explicit-Barrier Net for Safe and Scalable Robot Learning
Wei Xiao, Johnson Tsun-Hsuan Wang, Chuang Gan et al.
Towards Better-than-2 Approximation for Constrained Correlation Clustering
Andreas Kalavas, Evangelos Kipouridis, Nithin Varma
On the Error-Propagation of Inexact Hotelling's Deflation for Principal Component Analysis
Fangshuo Liao, J. Lyle Kim, Cruz Barnum et al.
Graph Geometry-Preserving Autoencoders
Jungbin Lim, Jihwan Kim, Yonghyeon Lee et al.
Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning Models
Xingyu Chen, Jiahao Xu, Tian Liang et al.
Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC
Wu Lin, Felix Dangel, Runa Eschenhagen et al.
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton
Chengmei Niu, Zhenyu Liao, Zenan Ling et al.
HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
Bor Jiun Lin, Chun-Yi Lee
The Underlying Universal Statistical Structure of Natural Datasets
Noam Levi, Yaron Oz
GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation
Haitao Lin, Lirong Wu, Yufei Huang et al.
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
In Huh, Changwook Jeong, Muhammad Alam
Offline Opponent Modeling with Truncated Q-driven Instant Policy Refinement
Yuheng Jing, Kai Li, Bingyun Liu et al.
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
Xixun Lin, Wenxiao Zhang, Fengzhao Shi et al.
SPMC: Self-Purifying Federated Backdoor Defense via Margin Contribution
Wenwen He, Wenke Huang, Bin Yang et al.
Towards Memorization Estimation: Fast, Formal and Free
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
Do We Really Need Message Passing in Brain Network Modeling?
Liang Yang, Yuwei Liu, Jiaming Zhuo et al.
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization
Zhuanghua Liu, Cheng Chen, Luo Luo et al.
ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection
Hongyu Liu, Runmin Cong, Hua Li et al.
GradPS: Resolving Futile Neurons in Parameter Sharing Network for Multi-Agent Reinforcement Learning
Haoyuan Qin, Zhengzhu Liu, Chenxing Lin et al.
Improving Model Alignment Through Collective Intelligence of Open-Source Models
Junlin Wang, Roy Xie, Shang Zhu et al.
ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via $\alpha$-$\beta$-Divergence
Guanghui Wang, Zhiyong Yang, Zitai Wang et al.
Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
RISHI JINKA, Venkata Sai Mothish Gonugunta, Deepak N. Subramani
Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation
Yuanwei Liu, Junwei Han, Xiwen Yao et al.
Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation
Jiashun Liu, Jianye Hao, Yi Ma et al.
ELTA: An Enhancer against Long-Tail for Aesthetics-oriented Models
Limin Liu, Shuai He, Anlong Ming et al.
On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors
Ruipeng Liu, Borui He, Naveed Tahir et al.
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
Xinyu Yang, Tom Zollo, Benjamin Eyre et al.
Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy
Yi Liu, Qirui Hu, Linglong Kong
Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents
Zhihan Liu, Hao Hu, Shenao Zhang et al.
Disparate Conditional Prediction in Multiclass Classifiers
Sivan Sabato, Eran Treister, Elad Yom-Tov
DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications
Ibrahim Fayad, Max Zimmer, Martin Schwartz et al.
Convergence of Online Learning Algorithm for a Mixture of Multiple Linear Regressions
Yujing Liu, Zhixin Liu, Lei Guo
Trustworthy Machine Learning through Data-Specific Indistinguishability
Hanshen Xiao, Zhen Yang, Edward Suh
Symmetry-Aware GFlowNets
Hohyun Kim, Seunggeun Lee, Min-hwan Oh
A Non-isotropic Time Series Diffusion Model with Moving Average Transitions
Chenxi Wang, Linxiao Yang, Zhixian Wang et al.
Feature Importance Metrics in the Presence of Missing Data
Henrik von Kleist, Joshua Wendland, Ilya Shpitser et al.
One Meta-tuned Transformer is What You Need for Few-shot Learning
Xu Yang, Huaxiu Yao, Ying WEI
Position: Language model developers should report train-test overlap
Andy Zhang, Kevin Klyman, Yifan Mai et al.
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
Qinshuo Liu, Zixin Wang, Xi'an Li et al.
High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails
Langqi Liu, Yibo Wang, Lijun Zhang
Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition
Yicheng Liu, Jie Wen, Chengliang Liu et al.
Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
Huafeng Liu, Yiran Fu, Liping Jing et al.
Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning
Biao Liu, Ning Xu, Xiangyu Fang et al.
Causality Based Front-door Defense Against Backdoor Attack on Language Models
Yiran Liu, Xiaoang Xu, Zhiyi Hou et al.
Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling
Chengliang Liu, Gehui Xu, Jie Wen et al.
Building Socially-Equitable Public Models
Yejia Liu, Jianyi Yang, Pengfei Li et al.
Positive-unlabeled AUC Maximization under Covariate Shift
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi et al.
TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
Qihe Huang, Zhengyang Zhou, Kuo Yang et al.
Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
Yunfei Long, Zilin Tian, Liguo Zhang et al.
Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
Yunyi Shen, Hao Sun, Jean-Francois Ton
On Explaining Equivariant Graph Networks via Improved Relevance Propagation
Hongyi Ling, Haiyang Yu, Zhimeng Jiang et al.
Stabilizing Sample Similarity in Representation via Mitigating Random Consistency
Jieting Wang, ZhangZelong Zhang, Feijiang Li et al.
Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training
Lin Lu, Chenxi Dai, Wangcheng Tao et al.
$\texttt{I$^2$MoE}$: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng et al.
Variance as a Catalyst: Efficient and Transferable Semantic Erasure Adversarial Attack for Customized Diffusion Models
Jiachen Yang, Yusong Wang, Yanmei Fang et al.
Modalities Contribute Unequally: Enhancing Medical Multi-modal Learning through Adaptive Modality Token Re-balancing
Jie Peng, Jenna Ballard, Mohan Zhang et al.
CauDiTS: Causal Disentangled Domain Adaptation of Multivariate Time Series
Junxin Lu, Shiliang Sun
CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation
Thibaud Southiratn, Bonil Koo, Yijingxiu Lu et al.
Demeaned Sparse: Efficient Anomaly Detection by Residual Estimate
Yifan Fang, Yifei Fang, Ruizhe Chen et al.
Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression
Zhankun Luo, Abolfazl Hashemi
Discrete and Continuous Difference of Submodular Minimization
George Orfanides, Tim Hoheisel, Marwa El Halabi
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
Bingshan Hu, Zhiming Huang, Tianyue Zhang et al.
Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data
Wenxi Lv, Qinliang Su, Hai Wan et al.
QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles for model-monitoring
Nikhil Pratap Ghanathe, Steve Wilton
Perceptually Constrained Precipitation Nowcasting Model
Wenzhi Feng, Xutao Li, Zhe Wu et al.
Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models
Junlong Lyu, Zhitang Chen, Shoubo Feng
Auto-reconfiguration for Latency Minimization in CPU-based DNN Serving
Ankit Bhardwaj, Amar Phanishayee, Deepak Narayanan et al.
RobustZero: Enhancing MuZero Reinforcement Learning Robustness to State Perturbations
Yushuai Li, Hengyu Liu, Torben Pedersen et al.
Outlier-aware Slicing for Post-Training Quantization in Vision Transformer
Yuexiao Ma, Huixia Li, Xiawu Zheng et al.
Diffusion Instruction Tuning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran et al.
Robust Automatic Modulation Classification with Fuzzy Regularization
Xinyan Liang, Ruijie Sang, Yuhua Qian et al.
High-dimensional Linear Bandits with Knapsacks
Wanteng Ma, Dong Xia, Jiashuo Jiang
Deep Sturm–Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions
David Vigouroux, Joseba Dalmau, Louis Béthune et al.
Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries
Xuening Feng, Zhaohui Jiang, Timo Kaufmann et al.
A Provable Decision Rule for Out-of-Distribution Detection
Xinsong Ma, Xin Zou, Weiwei Liu
Sample Complexity of Branch-length Estimation by Maximum Likelihood
David Clancy, Hanbaek Lyu, Sebastien Roch
Generalization Performance of Ensemble Clustering: From Theory to Algorithm
Xu Zhang, Haoye Qiu, Weixuan Liang et al.
More Than Meets the Eye: Enhancing Multi-Object Tracking Even with Prolonged Occlusions
Bishoy Galoaa, Somaieh Amraee, Sarah Ostadabbas
Best Subset Selection: Optimal Pursuit for Feature Selection and Elimination
Zhihan Zhu, Yanhao Zhang, Yong Xia
MetricEmbedding: Accelerate Metric Nearness by Tropical Inner Product
Muyang Cao, Jiajun Yu, Xin Du et al.
CoSER: Coordinating LLM-Based Persona Simulation of Established Roles
Xintao Wang, Heng Wang, Yifei Zhang et al.
Learning Imbalanced Data with Beneficial Label Noise
Guangzheng Hu, Feng Liu, Mingming Gong et al.
DexScale: Automating Data Scaling for Sim2Real Generalizable Robot Control
Guiliang Liu, Yueci Deng, Runyi Zhao et al.
IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck
Tian Bian, Yifan Niu, Chaohao Yuan et al.
Towards characterizing the value of edge embeddings in Graph Neural Networks
Dhruv Rohatgi, Tanya Marwah, Zachary Lipton et al.
Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques
Alon Arad, Saharon Rosset
Compressing tree ensembles through Level-wise Optimization and Pruning
Laurens Devos, Timo Martens, Deniz Oruc et al.
Label Distribution Propagation-based Label Completion for Crowdsourcing
Tong Wu, Liangxiao Jiang, Wenjun Zhang et al.
Decision-aware Training of Spatiotemporal Forecasting Models to Select a Top-K Subset of Sites for Intervention
Kyle Heuton, Frederick Muench, Shikhar Shrestha et al.
One Arrow, Two Hawks: Sharpness-aware Minimization for Federated Learning via Global Model Trajectory
Yuhang Li, Tong Liu, Yangguang Cui et al.
Confounder-Free Continual Learning via Recursive Feature Normalization
Yash Shah, Camila Gonzalez, MohammadHassan Abbasi et al.
Extreme Value Policy Optimization for Safe Reinforcement Learning
Shiqing Gao, Yihang Zhou, Shuai Shao et al.
Prompt-to-Leaderboard: Prompt-Adaptive LLM Evaluations
Evan Frick, Connor Chen, Joseph Tennyson et al.
Cross-Modal Alignment via Variational Copula Modelling
Feng Wu, Tsai Hor Chan, Fuying Wang et al.
Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates
Yunfei Huang, David S. Greenberg
Sounding that Object: Interactive Object-Aware Image to Audio Generation
Tingle Li, Baihe Huang, Xiaobin Zhuang et al.
Average Sensitivity of Hierarchical $k$-Median Clustering
Shijie Li, Weiqiang He, Ruobing Bai et al.
Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
Shiqing Gao, Jiaxin Ding, Luoyi Fu et al.
Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
Ce Zhang, Yixin Han, Yafei Wang et al.
Graph Inverse Style Transfer for Counterfactual Explainability
Bardh Prenkaj, Efstratios Zaradoukas, Gjergji Kasneci
Demystifying Singular Defects in Large Language Models
Haoqi Wang, Tong Zhang, Mathieu Salzmann
OAK: Enriching Document Representations using Auxiliary Knowledge for Extreme Classification
Shikhar Mohan, Deepak Saini, Anshul Mittal et al.
DVI:A Derivative-based Vision Network for INR
RUNZHAO YANG, Xiaolong Wu, Zhihong Zhang et al.
Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks
Bjørn Leth Møller, Christian Igel, Kristoffer Wickstrøm et al.
Preference Controllable Reinforcement Learning with Advanced Multi-Objective Optimization
Yucheng Yang, Tianyi Zhou, Mykola Pechenizkiy et al.
Generalized additive models via direct optimization of regularized decision stump forests
Magzhan Gabidolla, Miguel Carreira-Perpinan
A Peer-review Look on Multi-modal Clustering: An Information Bottleneck Realization Method
Zhengzheng Lou, Hang Xue, Chaoyang Zhang et al.
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
Chandra Mouli Sekar, Danielle Robinson, Shima Alizadeh et al.
DyCodeEval: Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data Contamination
Simin Chen, Pranav Pusarla, Baishakhi Ray
L-Diffusion: Laplace Diffusion for Efficient Pathology Image Segmentation
Weihan Li, Linyun Zhou, YangJian et al.
Weight matrices compression based on PDB model in deep neural networks
Xiaoling Wu, Junpeng Zhu, Zeng Li
Factored-Reward Bandits with Intermediate Observations
Marco Mussi, Simone Drago, Marcello Restelli et al.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs
Jie Hu, Yi-Ting Ma, Do-Young Eun
Learning in Deep Factor Graphs with Gaussian Belief Propagation
Seth Nabarro, Mark van der Wilk, Andrew Davison
Position: TrustLLM: Trustworthiness in Large Language Models
Yue Huang, Lichao Sun, Haoran Wang et al.
Density Ratio Estimation with Doubly Strong Robustness
Ryosuke Nagumo, Hironori Fujisawa
Uncertainty Quantification for LLM-Based Survey Simulations
Chengpiao Huang, Yuhang Wu, Kaizheng Wang
Safety Certificate against Latent Variables with Partially Unidentifiable Dynamics
Haoming Jing, Yorie Nakahira
SpikF: Spiking Fourier Network for Efficient Long-term Prediction
Wenjie Wu, Dexuan Huo, Hong Chen
Active feature acquisition via explainability-driven ranking
Osman Berke Guney, Ketan Saichandran, Karim Elzokm et al.
Novel Spectral Algorithms for the Partial Credit Model
Duc Nguyen, Anderson Zhang
The Polynomial Stein Discrepancy for Assessing Moment Convergence
Narayan Srinivasan, Matthew Sutton, Christopher Drovandi et al.
Risk-Sensitive Reward-Free Reinforcement Learning with CVaR
Xinyi Ni, Guanlin Liu, Lifeng Lai
Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs
Ziyu Ye, Rishabh Agarwal, Tianqi Liu et al.
Understanding the Impact of Introducing Constraints at Inference Time on Generalization Error
Masaaki Nishino, Kengo Nakamura, Norihito Yasuda
Modified K-means Algorithm with Local Optimality Guarantees
Mingyi Li, Michael R. Metel, Akiko Takeda
Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
Xinlei Niu, Christian Walder, Jing Zhang et al.
Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)
Kevin Wei, Patricia Paskov, Sunishchal Dev et al.
COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain Adaptation
Wenxu Wang, Rui Zhou, Jing Wang et al.
Position: Stop treating `AGI' as the north-star goal of AI research
Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li et al.
Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse Environments
Baohong Li, Yingrong Wang, Anpeng Wu et al.
Geometric Median (GM) Matching for Robust k-Subset Selection from Noisy Data
Anish Acharya, Sujay Sanghavi, Alex Dimakis et al.
MindCustomer: Multi-Context Image Generation Blended with Brain Signal
Muzhou Yu, Shuyun Lin, Lei Ma et al.
Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning
Eric Wang, Zhichao Chen, Haotian Wang et al.
Understanding Nonlinear Implicit Bias via Region Counts in Input Space
Jingwei Li, Jing Xu, Zifan Wang et al.
CPCF: A Cross-Prompt Contrastive Framework for Referring Multimodal Large Language Models
Lanyun Zhu, Deyi Ji, Tianrun Chen et al.
Procurement Auctions via Approximately Optimal Submodular Optimization
Yuan Deng, Amin Karbasi, Vahab Mirrokni et al.
Implicit Representations via Operator Learning
Sourav Pal, Harshavardhan Adepu, Clinton Wang et al.
Joint Metric Space Embedding by Unbalanced Optimal Transport with Gromov–Wasserstein Marginal Penalization
Florian Beier, Moritz Piening, Robert Beinert et al.
Exploring Vision Semantic Prompt for Efficient Point Cloud Understanding
Yixin Zha, Chuxin Wang, Wenfei Yang et al.
Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
Xiaokang Pan, Xingyu Li, Jin Liu et al.
RMIB: Representation Matching Information Bottleneck for Matching Text Representations
Haihui Pan, zhifang Liao, Wenrui Xie et al.
Linear convergence of Sinkhorn's algorithm for generalized static Schrödinger bridge
Rahul Choudhary, Hanbaek Lyu
sciLaMA: A Single-Cell Representation Learning Framework to Leverage Prior Knowledge from Large Language Models
Hongru Hu, Shuwen Zhang, Yongin Choi et al.
Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework
Guan Huang, Tao Shu
Revisiting Differentially Private Algorithms for Decentralized Online Learning
Xiaoyu Wang, Wenhao Yang, Chang Yao et al.
Mitigating Local Cohesion and Global Sparseness in Graph Contrastive Learning with Fuzzy Boundaries
Yuena Lin, Haichun Cai, Jun-Yi Hang et al.
State-Free Inference of State-Space Models: The *Transfer Function* Approach
Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro et al.
DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation
Shuyuan Wang, Philip D. Loewen, Michael Forbes et al.
Generalized Random Forests Using Fixed-Point Trees
David Fleischer, David A Stephens, Archer Yang
Position: Current Model Licensing Practices are Dragging Us into a Quagmire of Legal Noncompliance
Moming Duan, Mingzhe Du, Rui Zhao et al.
Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures
Alina Ene, Alessandro Epasto, Vahab Mirrokni et al.
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
Amit Peleg, Matthias Hein
Knowledge Distillation with Auxiliary Variable
Bo Peng, zhen fang, Guangquan Zhang et al.
A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings
Shib S Dasgupta, Michael Boratko, Andrew McCallum