Papers
Reconsidering Generative Objectives For Counterfactual Reasoning
Danni Lu, Chenyang Tao, Junya Chen et al.
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
Maximilian Balandat, Brian Karrer, Daniel Jiang et al.
Convergence and Stability of Graph Convolutional Networks on Large Random Graphs
Nicolas Keriven, Alberto Bietti, Samuel Vaiter
Active Structure Learning of Causal DAGs via Directed Clique Trees
Chandler Squires, Sara Magliacane, Kristjan Greenewald et al.
User-Dependent Neural Sequence Models for Continuous-Time Event Data
Alex Boyd, Robert Bamler, Stephan Mandt et al.
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them
Chen Liu, Mathieu Salzmann, Tao Lin et al.
Energy-based Out-of-distribution Detection
Weitang Liu, Xiaoyun Wang, John Owens et al.
A novel variational form of the Schatten-p quasi-norm
Paris Giampouras, Rene Vidal, Athanasios Rontogiannis et al.
Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters
Sulin Liu, Xingyuan Sun, Peter J. Ramadge et al.
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
No-regret Learning in Price Competitions under Consumer Reference Effects
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang
Avoiding Side Effects in Complex Environments
Alex Turner, Neale Ratzlaff, Prasad Tadepalli
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh, Nguyen Tran, Josh Nguyen
A Topological Filter for Learning with Label Noise
Pengxiang Wu, Songzhu Zheng, Mayank Goswami et al.
On the distance between two neural networks and the stability of learning
Jeremy Bernstein, Arash Vahdat, Yisong Yue et al.
ContraGAN: Contrastive Learning for Conditional Image Generation
Minguk Kang, Jaesik Park
How does Weight Correlation Affect Generalisation Ability of Deep Neural Networks?
Gaojie Jin, Xinping Yi, Liang Zhang et al.
The Statistical Cost of Robust Kernel Hyperparameter Turning
Raphael Meyer, Christopher Musco
A Group-Theoretic Framework for Data Augmentation
Shuxiao Chen, Edgar Dobriban, Jane Lee
Efficient Clustering for Stretched Mixtures: Landscape and Optimality
Kaizheng Wang, Yuling Yan, Mateo Diaz
RSKDD-Net: Random Sample-based Keypoint Detector and Descriptor
Fan Lu, Guang Chen, Yinlong Liu et al.
Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning
Pan Zhou, Jiashi Feng, Chao Ma et al.
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning
Jean-Bastien Grill, Florian Strub, Florent Altché et al.
Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality
Nian Si, Jose Blanchet, Soumyadip Ghosh et al.
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
Junhyung Park, Krikamol Muandet