Ioannis Ch. Paschalidis | DeepAI

AI Chat

Featured Co-authors

Hao Liu
150 publications
Jing Wang
124 publications
Jing Zhang
110 publications
Ashok Cutkosky
33 publications
Manjesh K. Hanawal
29 publications
Christos G. Cassandras
24 publications
Shi Pu
22 publications
Alex Olshevsky
19 publications
Henghui Zhu
19 publications
Christian Muise
14 publications
Yasaman Khazaeni
13 publications

∙ 01/31/2023

Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees

Robustness and safety are critical for the trustworthy deployment of dee...

0 James Queeney, et al. ∙

∙ 01/31/2023

Unconstrained Dynamic Regret via Sparse Coding

Motivated by time series forecasting, we study Online Linear Optimizatio...

0 Zhiyu Zhang, et al. ∙

∙ 11/29/2022

Closing the gap between SVRG and TD-SVRG with Gradient Splitting

Temporal difference (TD) learning is a simple algorithm for policy evalu...

0 Arsenii Mustafin, et al. ∙

∙ 10/15/2022

Distributionally Robust Multiclass Classification and Applications in Deep Image Classifiers

We develop a Distributionally Robust Optimization (DRO) formulation for ...

0 Ruidi Chen, et al. ∙

∙ 06/28/2022

Generalized Policy Improvement Algorithms with Theoretically Supported Sample Reuse

Real-world sequential decision making requires data-driven algorithms th...

0 James Queeney, et al. ∙

∙ 05/13/2022

Optimal Parameter-free Online Learning with Switching Cost

Parameter-freeness in online learning refers to the adaptivity of an alg...

0 Zhiyu Zhang, et al. ∙

∙ 03/11/2022

Learning from humans: combining imitation and deep reinforcement learning to accomplish human-level performance on a virtual foraging task

We develop a method to learn bio-inspired foraging policies using human ...

0 Vittorio Giammarino, et al. ∙

∙ 11/05/2021

Predicting Antimicrobial Resistance in the Intensive Care Unit

Antimicrobial resistance (AMR) is a risk for patients and a burden for t...

0 Taiyao Wang, et al. ∙

∙ 10/29/2021

Generalized Proximal Policy Optimization with Sample Reuse

In real-world decision making tasks, it is critical for data-driven rein...

0 James Queeney, et al. ∙

∙ 08/20/2021

Distributionally Robust Learning

This monograph develops a comprehensive statistical learning framework t...

0 Ruidi Chen, et al. ∙

∙ 06/09/2021

Communication-efficient SGD: From Local SGD to One-Shot Averaging

We consider speeding up stochastic gradient descent (SGD) by parallelizi...

10 Artin Spiridonoff, et al. ∙

∙ 03/22/2021

Online Baum-Welch algorithm for Hierarchical Imitation Learning

The options framework for hierarchical reinforcement learning has increa...

0 Vittorio Giammarino, et al. ∙

∙ 02/02/2021

Strongly Adaptive OCO with Memory

Recent progress in online control has popularized online learning with m...

7 Zhiyu Zhang, et al. ∙

∙ 12/19/2020

Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach

In order for reinforcement learning techniques to be useful in real-worl...

0 James Queeney, et al. ∙

∙ 07/09/2020

Explainability of Intelligent Transportation Systems using Knowledge Compilation: a Traffic Light Controller Case

Usage of automated controllers which make decisions on an environment ar...

0 Salomón Wollenstein-Betech, et al. ∙

∙ 06/10/2020

Robust Grouped Variable Selection Using Distributionally Robust Optimization

We propose a Distributionally Robust Optimization (DRO) formulation with...

0 Ruidi Chen, et al. ∙

∙ 06/10/2020

Robustified Multivariate Regression and Classification Using Distributionally Robust Optimization under the Wasserstein Metric

We develop Distributionally Robust Optimization (DRO) formulations for M...

0 Ruidi Chen, et al. ∙

∙ 06/03/2020

Local SGD With a Communication Overhead Depending Only on the Number of Workers

We consider speeding up stochastic gradient descent (SGD) by parallelizi...

6 Artin Spiridonoff, et al. ∙

∙ 06/28/2019

Asymptotic Network Independence in Distributed Optimization for Machine Learning

We provide a discussion of several recent results which have overcome a ...

0 Alex Olshevsky, et al. ∙

∙ 06/06/2019

A Non-Asymptotic Analysis of Network Independence for Distributed Stochastic Gradient Descent

This paper is concerned with minimizing the average of n cost functions ...

0 Alex Olshevsky, et al. ∙

∙ 03/21/2019

Convergence of Parameter Estimates for Regularized Mixed Linear Regression Models

We consider Mixed Linear Regression (MLR), where training data have bee...

0 Taiyao Wang, et al. ∙

∙ 03/21/2019

Prescriptive Cluster-Dependent Support Vector Machines with an Application to Reducing Hospital Readmissions

We augment linear Support Vector Machine (SVM) classifiers by adding thr...

0 Taiyao Wang, et al. ∙

∙ 10/24/2018

Clinical Concept Extraction with Contextual Word Embedding

Automatic extraction of clinical concepts is an essential step for turni...

0 Henghui Zhu, et al. ∙

∙ 01/03/2018

Predicting Chronic Disease Hospitalizations from Electronic Health Records: An Interpretable Classification Approach

Urban living in modern large cities has significant adverse effects on h...

0 Theodora S. Brisimi, et al. ∙

∙ 06/07/2017

Outlier Detection Using Distributionally Robust Optimization under the Wasserstein Metric

We present a Distributionally Robust Optimization (DRO) approach to outl...

0 Ruidi Chen, et al. ∙

∙ 02/27/2017

Statistical Anomaly Detection via Composite Hypothesis Testing for Markov Models

Under Markovian assumptions, we leverage a Central Limit Theorem (CLT) f...

0 Jing Zhang, et al. ∙

∙ 01/21/2017

Learning Policies for Markov Decision Processes from Data

We consider the problem of learning a policy for a Markov decision proce...

0 Manjesh K. Hanawal, et al. ∙

∙ 09/19/2013

Network Anomaly Detection: A Survey and Comparative Analysis of Stochastic and Deterministic Methods

We present five methods to the problem of network anomaly detection. The...

0 Jing Wang, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world