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03/23/2023
Preference-Aware Constrained Multi-Objective Bayesian Optimization
This paper addresses the problem of constrained multi-objective optimiza...
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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...
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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...
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07/09/2022
Dynamic Time Warping based Adversarial Framework for Time-Series Domain
Despite the rapid progress on research in adversarial robustness of deep...
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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...
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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...
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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...
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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...
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04/12/2022
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization
We consider the problem of multi-objective (MO) blackbox optimization us...
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01/16/2022
Adaptive Energy Management for Self-Sustainable Wearables in Mobile Health
Wearable devices that integrate multiple sensors, processors, and commun...
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12/02/2021
Bayesian Optimization over Permutation Spaces
Optimizing expensive to evaluate black-box functions over an input space...
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11/17/2021
ReaLPrune: ReRAM Crossbar-aware Lottery Ticket Pruned CNNs
Training machine learning (ML) models at the edge (on-chip training on e...
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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...
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10/13/2021
Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization
We consider the problem of black-box multi-objective optimization (MOO) ...
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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...
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06/08/2021
Bayesian Optimization over Hybrid Spaces
We consider the problem of optimizing hybrid structures (mixture of disc...
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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...
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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 (...
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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...
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12/14/2020
Mercer Features for Efficient Combinatorial Bayesian Optimization
Bayesian optimization (BO) is an efficient framework for solving black-b...
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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...
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11/30/2020
HeM3D: Heterogeneous Manycore Architecture Based on Monolithic 3D Vertical Integration
Heterogeneous manycore architectures are the key to efficiently execute ...
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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...
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09/12/2020
Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations
Many real-world applications involve black-box optimization of multiple ...
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09/01/2020
Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
We consider the problem of constrained multi-objective blackbox optimiza...
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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...
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08/18/2020
Scalable Combinatorial Bayesian Optimization with Tractable Statistical models
We study the problem of optimizing expensive blackbox functions over com...
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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...
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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 ...
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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...
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12/15/2019
One-Shot Induction of Generalized Logical Concepts via Human Guidance
We consider the problem of learning generalized first-order representati...
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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...
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01/23/2019
Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability
Anomaly detection (AD) task corresponds to identifying the true anomalie...
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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...
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10/02/2018
GLAD: GLocalized Anomaly Detection via Active Feature Space Suppression
We propose an algorithm called GLAD (GLocalized Anomaly Detection) that ...
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09/17/2018
Active Anomaly Detection via Ensembles
In critical applications of anomaly detection including computer securit...
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09/11/2018
Learning Scripts as Hidden Markov Models
Scripts have been proposed to model the stereotypical event sequences fo...
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01/21/2018
Learning to Speed Up Query Planning in Graph Databases
Querying graph structured data is a fundamental operation that enables i...
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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 ...
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11/30/2017
Machine Learning and Manycore Systems Design: A Serendipitous Symbiosis
Tight collaboration between experts of machine learning and manycore sys...
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06/27/2012