Papers
Efficiently avoiding saddle points with zero order methods: No gradients required
Emmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Georgios Piliouras
Efficiently escaping saddle points on manifolds
Christopher Criscitiello, Nicolas Boumal
Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy
Jonathan Ullman, Adam Sealfon
Efficiently Learning Fourier Sparse Set Functions
Andisheh Amrollahi, Amir Zandieh, Michael Kapralov et al.
Efficient Meta Learning via Minibatch Proximal Update
Pan Zhou, Xiaotong Yuan, Huan Xu et al.
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models
Aditya Gangrade, Praveen Venkatesh, Bobak Nazer et al.
Efficient Neural Architecture Transformation Search in Channel-Level for Object Detection
Junran Peng, Ming Sun, ZHAO-XIANG ZHANG et al.
Efficient online learning with kernels for adversarial large scale problems
Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Atilim Gunes Baydin, Lei Shao, Wahid Bhimji et al.
Efficient Pure Exploration in Adaptive Round model
Tianyuan Jin, Jieming SHI, Xiaokui Xiao et al.
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium
Gabriele Farina, Chun Kai Ling, Fei Fang et al.
Efficient Rematerialization for Deep Networks
Ravi Kumar, Manish Purohit, Zoya Svitkina et al.
Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent
Wenqing Hu, Chris Junchi Li, Xiangru Lian et al.
Efficient Symmetric Norm Regression via Linear Sketching
Zhao Song, Ruosong Wang, Lin Yang et al.
Elliptical Perturbations for Differential Privacy
Matthew Reimherr, Jordan Awan
Embedding Symbolic Knowledge into Deep Networks
Yaqi Xie, Ziwei Xu, Mohan S Kankanhalli et al.
Emergence of Object Segmentation in Perturbed Generative Models
Adam Bielski, Paolo Favaro
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
Saeed Mahloujifar, Xiao Zhang, Mohammad Mahmoody et al.
Enabling hyperparameter optimization in sequential autoencoders for spiking neural data
Mohammad Reza Keshtkaran, Chethan Pandarinath
End to end learning and optimization on graphs
Bryan Wilder, Eric Ewing, Bistra Dilkina et al.
End-to-End Learning on 3D Protein Structure for Interface Prediction
Raphael Townshend, Rishi Bedi, Patricia Suriana et al.
Energy-Inspired Models: Learning with Sampler-Induced Distributions
John Lawson, George Tucker, Bo Dai et al.
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
Shiyang Li, Xiaoyong Jin, Yao Xuan et al.
Envy-Free Classification
Maria-Florina F Balcan, Travis Dick, Ritesh Noothigattu et al.
Episodic Memory in Lifelong Language Learning
Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong et al.