Summary of Variable Selection in Convex Piecewise Linear Regression, by Haitham Kanj et al.
Variable Selection in Convex Piecewise Linear Regressionby Haitham Kanj, Seonho Kim, Kiryung LeeFirst submitted to…
Summary of Robust Sparse Regression with Non-isotropic Designs, by Chih-hung Liu et al.
Robust Sparse Regression with Non-Isotropic Designsby Chih-Hung Liu, Gleb NovikovFirst submitted to arxiv on: 31…
Summary of Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis, by Jiayu Su et al.
Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysisby Jiayu Su, David A. Knowles,…
Summary of On the Role Of Depth and Looping For In-context Learning with Task Diversity, by Khashayar Gatmiry et al.
On the Role of Depth and Looping for In-Context Learning with Task Diversityby Khashayar Gatmiry,…
Summary of Refined Risk Bounds For Unbounded Losses Via Transductive Priors, by Jian Qian et al.
Refined Risk Bounds for Unbounded Losses via Transductive Priorsby Jian Qian, Alexander Rakhlin, Nikita ZhivotovskiyFirst…
Summary of Predicting Mortality and Functional Status Scores Of Traumatic Brain Injury Patients Using Supervised Machine Learning, by Lucas Steinmetz et al.
Predicting Mortality and Functional Status Scores of Traumatic Brain Injury Patients using Supervised Machine Learningby…
Summary of Noise-aware Differentially Private Variational Inference, by Talal Alrawajfeh et al.
Noise-Aware Differentially Private Variational Inferenceby Talal Alrawajfeh, Joonas Jälkö, Antti HonkelaFirst submitted to arxiv on:…
Summary of Limit Theorems For Stochastic Gradient Descent with Infinite Variance, by Jose Blanchet et al.
Limit Theorems for Stochastic Gradient Descent with Infinite Varianceby Jose Blanchet, Aleksandar Mijatović, Wenhao YangFirst…
Summary of In-context Learning For Mixture Of Linear Regressions: Existence, Generalization and Training Dynamics, by Yanhao Jin et al.
In-context Learning for Mixture of Linear Regressions: Existence, Generalization and Training Dynamicsby Yanhao Jin, Krishnakumar…
Summary of State-space Models Can Learn In-context by Gradient Descent, By Neeraj Mohan Sushma et al.
State-space models can learn in-context by gradient descentby Neeraj Mohan Sushma, Yudou Tian, Harshvardhan Mestha,…