Summary of Less Is More: Rethinking Few-shot Learning and Recurrent Neural Nets, by Deborah Pereg et al.
Less is More: Rethinking Few-Shot Learning and Recurrent Neural Netsby Deborah Pereg, Martin Villiger, Brett…
Summary of Is Out-of-distribution Detection Learnable?, by Zhen Fang et al.
Is Out-of-Distribution Detection Learnable?by Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng…
Summary of Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learning, by Danial Dervovic and Nicolas Marchesotti and Freddy Lecue and Daniele Magazzeni
Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learningby Danial Dervovic,…
Summary of Bayes-optimal Classifiers Under Group Fairness, by Xianli Zeng and Edgar Dobriban and Guang Cheng
Bayes-Optimal Classifiers under Group Fairnessby Xianli Zeng, Edgar Dobriban, Guang ChengFirst submitted to arxiv on:…
Summary of Ethereum Fraud Detection with Heterogeneous Graph Neural Networks, by Hiroki Kanezashi et al.
Ethereum Fraud Detection with Heterogeneous Graph Neural Networksby Hiroki Kanezashi, Toyotaro Suzumura, Xin Liu, Takahiro…
Summary of Nips 2016 Tutorial: Generative Adversarial Networks, by Ian Goodfellow
NIPS 2016 Tutorial: Generative Adversarial Networksby Ian GoodfellowFirst submitted to arxiv on: 31 Dec 2016CategoriesMain:…
Summary of On Gradient Descent Ascent For Nonconvex-concave Minimax Problems, by Tianyi Lin et al.
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problemsby Tianyi Lin, Chi Jin, Michael I. JordanFirst…
Summary of Stochastic Bandits with Linear Constraints, by Aldo Pacchiano et al.
Stochastic Bandits with Linear Constraintsby Aldo Pacchiano, Mohammad Ghavamzadeh, Peter Bartlett, Heinrich JiangFirst submitted to…
Summary of Openstreetmap: Challenges and Opportunities in Machine Learning and Remote Sensing, by John Vargas et al.
OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensingby John Vargas, Shivangi Srivastava, Devis…
Summary of The Modern Mathematics Of Deep Learning, by Julius Berner et al.
The Modern Mathematics of Deep Learningby Julius Berner, Philipp Grohs, Gitta Kutyniok, Philipp PetersenFirst submitted…