Mehrdad Farajtabar | DeepAI

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∙ 03/15/2023

Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement

We propose Dataset Reinforcement, a strategy to improve a dataset once s...

0 Fartash Faghri, et al. ∙

∙ 07/05/2022

An Empirical Study of Implicit Regularization in Deep Offline RL

Deep neural networks are the most commonly used function approximators i...

12 Caglar Gulcehre, et al. ∙

∙ 02/20/2022

Efficient Continual Learning Ensembles in Neural Network Subspaces

A growing body of research in continual learning focuses on the catastro...

5 Thang Doan, et al. ∙

∙ 02/01/2022

Architecture Matters in Continual Learning

A large body of research in continual learning is devoted to overcoming ...

0 Seyed-Iman Mirzadeh, et al. ∙

∙ 10/21/2021

Wide Neural Networks Forget Less Catastrophically

A growing body of research in continual learning is devoted to overcomin...

0 Seyed-Iman Mirzadeh, et al. ∙

∙ 06/24/2021

Task-agnostic Continual Learning with Hybrid Probabilistic Models

Learning new tasks continuously without forgetting on a constantly chang...

0 Polina Kirichenko, et al. ∙

∙ 11/23/2020

Balance Regularized Neural Network Models for Causal Effect Estimation

Estimating individual and average treatment effects from observational d...

0 Mehrdad Farajtabar, et al. ∙

∙ 10/09/2020

Linear Mode Connectivity in Multitask and Continual Learning

Continual (sequential) training and multitask (simultaneous) training ar...

0 Seyed-Iman Mirzadeh, et al. ∙

∙ 10/06/2020

The Effectiveness of Memory Replay in Large Scale Continual Learning

We study continual learning in the large scale setting where tasks in th...

0 Yogesh Balaji, et al. ∙

∙ 06/19/2020

SOLA: Continual Learning with Second-Order Loss Approximation

Neural networks have achieved remarkable success in many cognitive tasks...

17 Dong Yin, et al. ∙

∙ 06/17/2020

A maximum-entropy approach to off-policy evaluation in average-reward MDPs

This work focuses on off-policy evaluation (OPE) with function approxima...

0 Nevena Lazic, et al. ∙

∙ 06/12/2020

Understanding the Role of Training Regimes in Continual Learning

Catastrophic forgetting affects the training of neural networks, limitin...

0 Seyed-Iman Mirzadeh, et al. ∙

∙ 06/10/2020

Learning to Incentivize Other Learning Agents

The challenge of developing powerful and general Reinforcement Learning ...

0 Jiachen Yang, et al. ∙

∙ 04/24/2020

Dropout as an Implicit Gating Mechanism For Continual Learning

In recent years, neural networks have demonstrated an outstanding abilit...

0 Seyed-Iman Mirzadeh, et al. ∙

∙ 02/13/2020

Self-Distillation Amplifies Regularization in Hilbert Space

Knowledge distillation introduced in the deep learning context is a meth...

15 Hossein Mobahi, et al. ∙

∙ 10/15/2019

Orthogonal Gradient Descent for Continual Learning

Neural networks are achieving state of the art and sometimes super-human...

13 Mehrdad Farajtabar, et al. ∙

∙ 06/13/2019

Cross-View Policy Learning for Street Navigation

The ability to navigate from visual observations in unfamiliar environme...

5 Ang Li, et al. ∙

∙ 02/09/2019

Improved Knowledge Distillation via Teacher Assistant: Bridging the Gap Between Student and Teacher

Despite the fact that deep neural networks are powerful models and achie...

22 Seyed-Iman Mirzadeh, et al. ∙

∙ 02/10/2018

More Robust Doubly Robust Off-policy Evaluation

We study the problem of off-policy evaluation (OPE) in reinforcement lea...

0 Mehrdad Farajtabar, et al. ∙

∙ 12/12/2017

Hawkes Processes for Invasive Species Modeling and Management

The spread of invasive species to new areas threatens the stability of e...

0 Amrita Gupta, et al. ∙

∙ 05/23/2017

Wasserstein Learning of Deep Generative Point Process Models

Point processes are becoming very popular in modeling asynchronous seque...

0 Shuai Xiao, et al. ∙

∙ 03/04/2017

Recurrent Poisson Factorization for Temporal Recommendation

Poisson factorization is a probabilistic model of users and items for re...

0 Seyed Abbas Hosseini, et al. ∙

∙ 10/24/2016

Distilling Information Reliability and Source Trustworthiness from Digital Traces

Online knowledge repositories typically rely on their users or dedicated...

0 Behzad Tabibian, et al. ∙

∙ 05/22/2016

Smart broadcasting: Do you want to be seen?

Many users in online social networks are constantly trying to gain atten...

0 Mohammad Reza Karimi, et al. ∙

∙ 03/29/2016

Detecting weak changes in dynamic events over networks

Large volume of networked streaming event data are becoming increasingly...

0 Shuang Li, et al. ∙

∙ 02/14/2016

Learning Granger Causality for Hawkes Processes

Learning Granger causality for general point processes is a very challen...

0 Hongteng Xu, et al. ∙

∙ 07/08/2015

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution

Information diffusion in online social networks is affected by the under...

0 Mehrdad Farajtabar, et al. ∙