Papers
From Importance Sampling to Doubly Robust Policy Gradient
Jiawei Huang, Nan Jiang
From Local SGD to Local Fixed-Point Methods for Federated Learning
Grigory Malinovskiy, Dmitry Kovalev, Elnur Gasanov et al.
From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model
Aadirupa Saha, Aditya Gopalan
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models
Aytunc Sahin, Yatao Bian, Joachim Buhmann et al.
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training
Yuji Roh, Kangwook Lee, Steven Whang et al.
Frustratingly Simple Few-Shot Object Detection
Xin Wang, Thomas Huang, Joseph Gonzalez et al.
Full Law Identification in Graphical Models of Missing Data: Completeness Results
Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser
Fully Parallel Hyperparameter Search: Reshaped Space-Filling
Marie-Liesse Cauwet, Camille Couprie, Julien Dehos et al.
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations
Florian Tramer, Jens Behrmann, Nicholas Carlini et al.
Gamification of Pure Exploration for Linear Bandits
Rémy Degenne, Pierre Menard, Xuedong Shang et al.
Generalisation error in learning with random features and the hidden manifold model
Federica Gerace, Bruno Loureiro, Florent Krzakala et al.
Generalization and Representational Limits of Graph Neural Networks
Vikas Garg, Stefanie Jegelka, Tommi Jaakkola
Generalization Error of Generalized Linear Models in High Dimensions
Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit et al.
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features
Liang Ding, Rui Tuo, Shahin Shahrampour
Generalization to New Actions in Reinforcement Learning
Ayush Jain, Andrew Szot, Joseph Lim
Generalized and Scalable Optimal Sparse Decision Trees
Jimmy Lin, Chudi Zhong, Diane Hu et al.
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data
Marc Finzi, Samuel Stanton, Pavel Izmailov et al.
Generating Programmatic Referring Expressions via Program Synthesis
Jiani Huang, Calvin Smith, Osbert Bastani et al.
Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate
Yufeng Zhang, Qi Cai, Zhuoran Yang et al.
Generative Flows with Matrix Exponential
Changyi Xiao, Ligang Liu
Generative Pretraining From Pixels
Mark Chen, Alec Radford, Rewon Child et al.
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
Felipe Petroski Such, Aditya Rawal, Joel Lehman et al.
Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models
Yiding Feng, Ekaterina Khmelnitskaya, Denis Nekipelov
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
Marc Brockschmidt
Goal-Aware Prediction: Learning to Model What Matters
Suraj Nair, Silvio Savarese, Chelsea Finn