research
∙
05/18/2023
Riemannian Multiclass Logistics Regression for SPD Neural Networks
Deep neural networks for learning symmetric positive definite (SPD) matr...
share
research
∙
03/26/2023
Adaptive Riemannian Metrics on SPD Manifolds
Symmetric Positive Definite (SPD) matrices have received wide attention ...
research
∙
05/11/2022
RLOP: RL Methods in Option Pricing from a Mathematical Perspective
Abstract In this work, we build two environments, namely the modified QL...
research
∙
03/16/2022
AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension
Recent machine reading comprehension datasets such as ReClor and LogiQA ...
research
∙
10/22/2021
ReLACE: Reinforcement Learning Agent for Counterfactual Explanations of Arbitrary Predictive Models
The demand for explainable machine learning (ML) models has been growing...
research
∙
06/21/2021
Large deviations principles of sample paths and invariant measures of numerical methods for parabolic SPDEs
For parabolic stochastic partial differential equations (SPDEs), we show...
research
∙
02/14/2021
Costly Features Classification using Monte Carlo Tree Search
We consider the problem of costly feature classification, where we seque...
research
∙
11/11/2019
Item Response Theory based Ensemble in Machine Learning
In this article, we propose a novel probabilistic framework to improve t...
research
∙
10/04/2019
