Papers
4,025 papers found
Invertible Generative Modeling using Linear Rational Splines
Hadi Mohaghegh Dolatabadi, Sarah Erfani, Christopher Leckie
Ivy: Instrumental Variable Synthesis for Causal Inference
Zhaobin Kuang, Frederic Sala, Nimit Sohoni et al.
Kernel Conditional Density Operators
Ingmar Schuster, Mattes Mollenhauer, Stefan Klus et al.
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization
Poompol Buathong, David Ginsbourger, Tipaluck Krityakierne
Langevin Monte Carlo without smoothness
Niladri Chatterji, Jelena Diakonikolas, Michael I. Jordan et al.
Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis
Kaige Yang, Laura Toni, Xiaowen Dong
LdSM: Logarithm-depth Streaming Multi-label Decision Trees
Maryam Majzoubi, Anna Choromanska
Learnable Bernoulli Dropout for Bayesian Deep Learning
Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh et al.
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes
Zhaozhi Qian, Ahmed Alaa, Alexis Bellot et al.
Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification
Zhengjue Wang, Chaojie Wang, Hao Zhang et al.
Learning Entangled Single-Sample Distributions via Iterative Trimming
Hui Yuan, Yingyu Liang
Learning Fair Representations for Kernel Models
Zilong Tan, Samuel Yeom, Matt Fredrikson et al.
Learning Gaussian Graphical Models via Multiplicative Weights
Anamay Chaturvedi, Jonathan Scarlett
Learning Hierarchical Interactions at Scale: A Convex Optimization Approach
Hussein Hazimeh, Rahul Mazumder
Learning High-dimensional Gaussian Graphical Models under Total Positivity without Adjustment of Tuning Parameters
Yuhao Wang, Uma Roy, Caroline Uhler
Learning in Gated Neural Networks
Ashok Makkuva, Sewoong Oh, Sreeram Kannan et al.
Learning Overlapping Representations for the Estimation of Individualized Treatment Effects
Yao Zhang, Alexis Bellot, Mihaela Schaar
Learning piecewise Lipschitz functions in changing environments
Dravyansh Sharma, Maria-Florina Balcan, Travis Dick
Learning Rate Adaptation for Differentially Private Learning
Antti Koskela, Antti Honkela
Learning Sparse Nonparametric DAGs
Xun Zheng, Chen Dan, Bryon Aragam et al.
Learning spectrograms with convolutional spectral kernels
Zheyang Shen, Markus Heinonen, Samuel Kaski
Learning with minibatch Wasserstein : asymptotic and gradient properties
Kilian Fatras, Younes Zine, Rémi Flamary et al.
Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data
Måns Magnusson, Aki Vehtari, Johan Jonasson et al.
LIBRE: Learning Interpretable Boolean Rule Ensembles
Graziano Mita, Paolo Papotti, Maurizio Filippone et al.