Papers
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise
Thanh Huy Nguyen, Umut Simsekli, Mert Gurbuzbalaban et al.
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension
Carl-Johann Simon-Gabriel, Yann Ollivier, Leon Bottou et al.
First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems
Ching-Pei Lee, Stephen Wright
First order expansion of convex regularized estimators
Pierre Bellec, Arun Kuchibhotla
First-order methods almost always avoid saddle points: The case of vanishing step-sizes
Ioannis Panageas, Georgios Piliouras, Xiao Wang
First Order Motion Model for Image Animation
Aliaksandr Siarohin, Stéphane Lathuilière, Sergey Tulyakov et al.
First Steps towards Building a Medical Lexicon for Spanish with Linguistic and Semantic Information
Leonardo Campillos-Llanos
Fisher-Bures Adversary Graph Convolutional Networks
Ke Sun, Piotr Koniusz, Zhen Wang
Fisher Efficient Inference of Intractable Models
Song Liu, Takafumi Kanamori, Wittawat Jitkrittum et al.
Fisher Information and Natural Gradient Learning in Random Deep Networks
Shun-ichi Amari, Ryo Karakida, Masafumi Oizumi
Fisher-Rao Metric, Geometry, and Complexity of Neural Networks
Tengyuan Liang, Tomaso Poggio, Alexander Rakhlin et al.
Fitting Multiple Heterogeneous Models by Multi-Class Cascaded T-Linkage
Luca Magri, Andrea Fusiello
Fixed That for You: Generating Contrastive Claims with Semantic Edits
Christopher Hidey, Kathy McKeown
Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions
Chris Russell, Matteo Toso, Neill Campbell
Fixing Mini-batch Sequences with Hierarchical Robust Partitioning
Shengjie Wang, Wenruo Bai, Chandrashekhar Lavania et al.
Fixing the train-test resolution discrepancy
Hugo Touvron, Andrea Vedaldi, Matthijs Douze et al.
Fixup Initialization: Residual Learning Without Normalization
Hongyi Zhang, Yann N. Dauphin, Tengyu Ma
FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP
Alan Akbik, Tanja Bergmann, Duncan Blythe et al.
Flambé: A Customizable Framework for Machine Learning Experiments
Jeremy Wohlwend, Nicholas Matthews, Ivan Itzcovich
FLARe: Forecasting by Learning Anticipated Representations
Surya Teja Devarakonda, Joie Yeahuay Wu, Yi Ren Fung et al.
Flare in Interference-Based Hyperspectral Cameras
Eden Sassoon, Yoav Y. Schechner, Tali Treibitz
Flashield: a Hybrid Key-value Cache that Controls Flash Write Amplification
Assaf Eisenman, Asaf Cidon, Evgenya Pergament et al.
Flat Metric Minimization with Applications in Generative Modeling
Thomas Möllenhoff, Daniel Cremers
Flattening a Hierarchical Clustering through Active Learning
Fabio Vitale, Anand Rajagopalan, Claudio Gentile
FLEX: Faithful Linguistic Explanations for Neural Net Based Model Decisions
Sandareka Wickramanayake, Wynne Hsu, Mong Li Lee