Summary of Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory, by Arnulf Jentzen et al.
Mathematical Introduction to Deep Learning: Methods, Implementations, and Theoryby Arnulf Jentzen, Benno Kuckuck, Philippe von…
Summary of Predict-then-optimize by Proxy: Learning Joint Models Of Prediction and Optimization, By James Kotary et al.
Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimizationby James Kotary, Vincenzo Di Vito,…
Summary of Controlling Continuous Relaxation For Combinatorial Optimization, by Yuma Ichikawa
Controlling Continuous Relaxation for Combinatorial Optimizationby Yuma IchikawaFirst submitted to arxiv on: 29 Sep 2023CategoriesMain:…
Summary of When Monte-carlo Dropout Meets Multi-exit: Optimizing Bayesian Neural Networks on Fpga, by Hongxiang Fan and Hao Chen and Liam Castelli and Zhiqiang Que and He Li and Kenneth Long and Wayne Luk
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGAby Hongxiang Fan, Hao Chen,…
Summary of The Triad Of Failure Modes and a Possible Way Out, by Emanuele Sansone
The Triad of Failure Modes and a Possible Way Outby Emanuele SansoneFirst submitted to arxiv…
Summary of On the Global Convergence Of Natural Actor-critic with Two-layer Neural Network Parametrization, by Mudit Gaur et al.
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrizationby Mudit Gaur, Amrit…
Summary of Evolutionary Approaches to Explainable Machine Learning, by Ryan Zhou et al.
Evolutionary approaches to explainable machine learningby Ryan Zhou, Ting HuFirst submitted to arxiv on: 23…
Summary of Relationship Between Batch Size and Number Of Steps Needed For Nonconvex Optimization Of Stochastic Gradient Descent Using Armijo Line Search, by Yuki Tsukada et al.
Relationship between Batch Size and Number of Steps Needed for Nonconvex Optimization of Stochastic Gradient…
Summary of Constrained Online Two-stage Stochastic Optimization: Near Optimal Algorithms Via Adversarial Learning, by Jiashuo Jiang
Constrained Online Two-stage Stochastic Optimization: Near Optimal Algorithms via Adversarial Learningby Jiashuo JiangFirst submitted to…
Summary of Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds, by Shion Takeno et al.
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Boundsby Shion Takeno, Yu Inatsu,…