Janardhan Rao Doppa

research

∙ 03/23/2023

Preference-Aware Constrained Multi-Objective Bayesian Optimization

This paper addresses the problem of constrained multi-objective optimiza...

0 Alaleh Ahmadianshalchi, et al. ∙

research

∙ 03/03/2023

Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings

We consider the problem of optimizing expensive black-box functions over...

0 Aryan Deshwal, et al. ∙

research

∙ 07/10/2022

Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity Recognition

Increasingly, human behavior is captured on mobile devices, leading to a...

0 Janardhan Rao Doppa, et al. ∙

research

∙ 07/09/2022

Dynamic Time Warping based Adversarial Framework for Time-Series Domain

Despite the rapid progress on research in adversarial robustness of deep...

4 Taha Belkhouja, et al. ∙

research

∙ 07/09/2022

Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features

Time-series data arises in many real-world applications (e.g., mobile he...

0 Taha Belkhouja, et al. ∙

research

∙ 07/09/2022

Out-of-Distribution Detection in Time-Series Domain: A Novel Seasonal Ratio Scoring Approach

Safe deployment of time-series classifiers for real-world applications r...

9 Taha Belkhouja, et al. ∙

research

∙ 07/09/2022

Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis

Despite the success of deep neural networks (DNNs) for real-world applic...

19 Taha Belkhouja, et al. ∙

research

∙ 06/25/2022

Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach

The rising growth of deep neural networks (DNNs) and datasets in size mo...

0 Syrine Belakaria, et al. ∙

research

∙ 04/12/2022

Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization

We consider the problem of multi-objective (MO) blackbox optimization us...

0 Syrine Belakaria, et al. ∙

research

∙ 01/16/2022

Adaptive Energy Management for Self-Sustainable Wearables in Mobile Health

Wearable devices that integrate multiple sensors, processors, and commun...

0 Dina Hussein, et al. ∙

research

∙ 12/02/2021

Bayesian Optimization over Permutation Spaces

Optimizing expensive to evaluate black-box functions over an input space...

0 Aryan Deshwal, et al. ∙

research

∙ 11/17/2021

ReaLPrune: ReRAM Crossbar-aware Lottery Ticket Pruned CNNs

Training machine learning (ML) models at the edge (on-chip training on e...

0 Biresh Kumar Joardar, et al. ∙

research

∙ 11/01/2021

Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces

We consider the problem of optimizing combinatorial spaces (e.g., sequen...

0 Aryan Deshwal, et al. ∙

research

∙ 10/13/2021

Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization

We consider the problem of black-box multi-objective optimization (MOO) ...

0 Syrine Belakaria, et al. ∙

research

∙ 09/30/2021

CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning

Unsupervised domain adaptation (UDA) provides a strategy for improving m...

0 Janardhan Rao Doppa, et al. ∙

research

∙ 06/08/2021

Bayesian Optimization over Hybrid Spaces

We consider the problem of optimizing hybrid structures (mixture of disc...

0 Aryan Deshwal, et al. ∙

research

∙ 04/14/2021

Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs: An Information-Theoretic Approach

Mobile system-on-chips (SoCs) are growing in their complexity and hetero...

0 Aryan Deshwal, et al. ∙

research

∙ 03/23/2021

SETGAN: Scale and Energy Trade-off GANs for Image Applications on Mobile Platforms

We consider the task of photo-realistic unconditional image generation (...

0 Nitthilan Kannappan Jayakodi, et al. ∙

research

∙ 02/16/2021

ReGraphX: NoC-enabled 3D Heterogeneous ReRAM Architecture for Training Graph Neural Networks

Graph Neural Network (GNN) is a variant of Deep Neural Networks (DNNs) o...

0 Aqeeb Iqbal Arka, et al. ∙

research

∙ 12/14/2020

Mercer Features for Efficient Combinatorial Bayesian Optimization

Bayesian optimization (BO) is an efficient framework for solving black-b...

0 Aryan Deshwal, et al. ∙

research

∙ 12/14/2020

Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework

We consider the problem of optimizing expensive black-box functions over...

0 Aryan Deshwal, et al. ∙

research

∙ 11/30/2020

HeM3D: Heterogeneous Manycore Architecture Based on Monolithic 3D Vertical Integration

Heterogeneous manycore architectures are the key to efficiently execute ...

0 Aqeeb Iqbal Arka, et al. ∙

research

∙ 11/02/2020

Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach

We study the novel problem of blackbox optimization of multiple objectiv...

0 Syrine Belakaria, et al. ∙

research

∙ 09/12/2020

Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations

Many real-world applications involve black-box optimization of multiple ...

0 Syrine Belakaria, et al. ∙

research

∙ 09/01/2020

Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints

We consider the problem of constrained multi-objective blackbox optimiza...

0 Syrine Belakaria, et al. ∙

research

∙ 08/22/2020

Online Adaptive Learning for Runtime Resource Management of Heterogeneous SoCs

Dynamic resource management has become one of the major areas of researc...

0 Sumit K. Mandal, et al. ∙

research

∙ 08/18/2020

Scalable Combinatorial Bayesian Optimization with Tractable Statistical models

We study the problem of optimizing expensive blackbox functions over com...

0 Aryan Deshwal, et al. ∙

research

∙ 08/16/2020

Uncertainty aware Search Framework for Multi-Objective Bayesian Optimization with Constraints

We consider the problem of constrained multi-objective (MO) blackbox opt...

0 Syrine Belakaria, et al. ∙

research

∙ 05/22/2020

Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data

Domain adaptation (DA) offers a valuable means to reuse data and models ...

0 Janardhan Rao Doppa, et al. ∙

research

∙ 03/20/2020

An Energy-Aware Online Learning Framework for Resource Management in Heterogeneous Platforms

Mobile platforms must satisfy the contradictory requirements of fast res...

0 Sumit K. Mandal, et al. ∙

research

∙ 12/15/2019

One-Shot Induction of Generalized Logical Concepts via Human Guidance

We consider the problem of learning generalized first-order representati...

0 Mayukh Das, et al. ∙

research

∙ 01/29/2019

Trading-off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach

Deep neural networks have seen tremendous success for different modaliti...

0 Nitthilan Kannappan Jayakodi, et al. ∙

research

∙ 01/23/2019

Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability

Anomaly detection (AD) task corresponds to identifying the true anomalie...

0 Shubhomoy Das, et al. ∙

research

∙ 10/20/2018

Learning-based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems

The rising use of deep learning and other big-data algorithms has led to...

2 Biresh Kumar Joardar, et al. ∙

research

∙ 10/02/2018

GLAD: GLocalized Anomaly Detection via Active Feature Space Suppression

We propose an algorithm called GLAD (GLocalized Anomaly Detection) that ...

0 Shubhomoy Das, et al. ∙

research

∙ 09/17/2018

Active Anomaly Detection via Ensembles

In critical applications of anomaly detection including computer securit...

0 Shubhomoy Das, et al. ∙

research

∙ 09/11/2018

Learning Scripts as Hidden Markov Models

Scripts have been proposed to model the stereotypical event sequences fo...

0 J. Walker Orr, et al. ∙

research

∙ 01/21/2018

Learning to Speed Up Query Planning in Graph Databases

Querying graph structured data is a fundamental operation that enables i...

0 Mohammad Hossain Namaki, et al. ∙

research

∙ 12/05/2017

On-Chip Communication Network for Efficient Training of Deep Convolutional Networks on Heterogeneous Manycore Systems

Convolutional Neural Networks (CNNs) have shown a great deal of success ...

0 Wonje Choi, et al. ∙

research

∙ 11/30/2017

Machine Learning and Manycore Systems Design: A Serendipitous Symbiosis

Tight collaboration between experts of machine learning and manycore sys...

0 Ryan Gary Kim, et al. ∙

research

∙ 06/27/2012

Output Space Search for Structured Prediction

We consider a framework for structured prediction based on search in the...

0 Janardhan Rao Doppa, et al. ∙

Janardhan Rao Doppa

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