Papers
4,025 papers found
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors
Teodora Popordanoska, Sebastian Gregor Gruber, Aleksei Tiulpin et al.
Consistent Hierarchical Classification with A Generalized Metric
Yuzhou Cao, Lei Feng, Bo An
Consistent Optimal Transport with Empirical Conditional Measures
Piyushi Manupriya, Rachit K. Das, Sayantan Biswas et al.
Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication
Hugo Richard, Etienne Boursier, Vianney Perchet
Contextual Bandits with Budgeted Information Reveal
Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu et al.
Contextual Directed Acyclic Graphs
Ryan Thompson, Edwin V. Bonilla, Robert Kohn
Continual Domain Adversarial Adaptation via Double-Head Discriminators
Yan Shen, Zhanghexuan Ji, Chunwei Ma et al.
Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games
Jing Dong, Baoxiang Wang, Yaoliang Yu
Coreset Markov chain Monte Carlo
Naitong Chen, Trevor Campbell
Corruption-Robust Offline Two-Player Zero-Sum Markov Games
Andi Nika, Debmalya Mandal, Adish Singla et al.
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning
Amey P. Pasarkar, Adji Bousso Dieng
Cross-model Mutual Learning for Exemplar-based Medical Image Segmentation
Qing En, Yuhong Guo
Cylindrical Thompson Sampling for High-Dimensional Bayesian Optimization
Bahador Rashidi, Kerrick Johnstonbaugh, Chao Gao
DAGnosis: Localized Identification of Data Inconsistencies using Structures
Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat et al.
Data-Adaptive Probabilistic Likelihood Approximation for Ordinary Differential Equations
Mohan Wu, Martin Lysy
Data-Driven Confidence Intervals with Optimal Rates for the Mean of Heavy-Tailed Distributions
Ambrus Tamás, Szabolcs Szentpéteri, Balázs Csáji
Data-Driven Online Model Selection With Regret Guarantees
Chris Dann, Claudio Gentile, Aldo Pacchiano
Data Driven Threshold and Potential Initialization for Spiking Neural Networks
Velibor Bojkovic, Srinivas Anumasa, Giulia De Masi et al.
Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity
Siddharth Joshi, Arnav Jain, Ali Payani et al.
Deep anytime-valid hypothesis testing
Teodora Pandeva, Patrick Forré, Aaditya Ramdas et al.
Deep Classifier Mimicry without Data Access
Steven Braun, Martin Mundt, Kristian Kersting
Deep Dependency Networks and Advanced Inference Schemes for Multi-Label Classification
Shivvrat Arya, Yu Xiang, Vibhav Gogate
DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data
Taehyo Kim, Hai Shu, Qiran Jia et al.
Deep Learning-Based Alternative Route Computation
Alex Zhai, Dee Guo, Sreenivas Gollapudi et al.