Papers
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming
Chuan Wen, Jianing Qian, Jierui Lin et al.
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Xiang Li, Renyu Zhu, Yao Cheng et al.
Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks
Runpei Dong, Zhanhong Tan, Mengdi Wu et al.
Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications
Bokun Wang, Tianbao Yang
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
Andrew J Wagenmaker, Yifang Chen, Max Simchowitz et al.
Fisher SAM: Information Geometry and Sharpness Aware Minimisation
Minyoung Kim, Da Li, Shell X Hu et al.
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
Yuxin Wen, Jonas A. Geiping, Liam Fowl et al.
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
Alexandre Rame, Corentin Dancette, Matthieu Cord
FITNESS: (Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers
Abishek Sankararaman, Balakrishnan Narayanaswamy, Vikramank Y Singh et al.
Flashlight: Enabling Innovation in Tools for Machine Learning
Jacob D Kahn, Vineel Pratap, Tatiana Likhomanenko et al.
Flow-based Recurrent Belief State Learning for POMDPs
Xiaoyu Chen, Yao Mark Mu, Ping Luo et al.
Flowformer: Linearizing Transformers with Conservation Flows
Haixu Wu, Jialong Wu, Jiehui Xu et al.
Flow-Guided Sparse Transformer for Video Deblurring
Jing Lin, Yuanhao Cai, Xiaowan Hu et al.
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension
Bruno Loureiro, Cedric Gerbelot, Maria Refinetti et al.
FOCUS: Familiar Objects in Common and Uncommon Settings
Priyatham Kattakinda, Soheil Feizi
Forget-free Continual Learning with Winning Subnetworks
Haeyong Kang, Rusty John Lloyd Mina, Sultan Rizky Hikmawan Madjid et al.
For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria
Scott Emmons, Caspar Oesterheld, Andrew Critch et al.
Forward Operator Estimation in Generative Models with Kernel Transfer Operators
Zhichun Huang, Rudrasis Chakraborty, Vikas Singh
Fourier Learning with Cyclical Data
Yingxiang Yang, Zhihan Xiong, Tianyi Liu et al.
Framework for Evaluating Faithfulness of Local Explanations
Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz
FriendlyCore: Practical Differentially Private Aggregation
Eliad Tsfadia, Edith Cohen, Haim Kaplan et al.
From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers
Krzysztof Choromanski, Han Lin, Haoxian Chen et al.
From data to functa: Your data point is a function and you can treat it like one
Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami et al.
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
Daniil Tiapkin, Denis Belomestny, Eric Moulines et al.
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model
Heesun Bae, Seungjae Shin, Byeonghu Na et al.