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07/28/2023
VeriGen: A Large Language Model for Verilog Code Generation
In this study, we explore the capability of Large Language Models (LLMs)...
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07/27/2023
R-LPIPS: An Adversarially Robust Perceptual Similarity Metric
Similarity metrics have played a significant role in computer vision to ...
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07/11/2023
Differential Analysis of Triggers and Benign Features for Black-Box DNN Backdoor Detection
This paper proposes a data-efficient detection method for deep neural ne...
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06/16/2023
Towards Better Certified Segmentation via Diffusion Models
The robustness of image segmentation has been an important research topi...
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05/22/2023
Chip-Chat: Challenges and Opportunities in Conversational Hardware Design
Modern hardware design starts with specifications provided in natural la...
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05/22/2023
INVICTUS: Optimizing Boolean Logic Circuit Synthesis via Synergistic Learning and Search
Logic synthesis is the first and most vital step in chip design. This st...
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04/28/2023
Can deepfakes be created by novice users?
Recent advancements in machine learning and computer vision have led to ...
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03/07/2023
Path Planning Under Uncertainty to Localize mmWave Sources
In this paper, we study a navigation problem where a mobile robot needs ...
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03/06/2023
ALMOST: Adversarial Learning to Mitigate Oracle-less ML Attacks via Synthesis Tuning
Oracle-less machine learning (ML) attacks have broken various logic lock...
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02/22/2023
Precoding-oriented Massive MIMO CSI Feedback Design
Downlink massive multiple-input multiple-output (MIMO) precoding algorit...
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02/04/2023
A Minimax Approach Against Multi-Armed Adversarial Attacks Detection
Multi-armed adversarial attacks, in which multiple algorithms and object...
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02/02/2023
Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access
Fair machine learning methods seek to train models that balance model pe...
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12/16/2022
An Upper Bound for the Distribution Overlap Index and Its Applications
This paper proposes an easy-to-compute upper bound for the overlap index...
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12/13/2022
Benchmarking Large Language Models for Automated Verilog RTL Code Generation
Automating hardware design could obviate a significant amount of human e...
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12/13/2022
Privacy-Preserving Collaborative Learning through Feature Extraction
We propose a framework in which multiple entities collaborate to build a...
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08/20/2022
Security Implications of Large Language Model Code Assistants: A User Study
Advances in Deep Learning have led to the emergence of Large Language Mo...
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07/14/2022
Characterizing and Optimizing End-to-End Systems for Private Inference
Increasing privacy concerns have given rise to Private Inference (PI). I...
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06/29/2022
Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale
The success of DNNs is driven by the counter-intuitive ability of over-p...
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05/26/2022
Denial-of-Service Attacks on Learned Image Compression
Deep learning techniques have shown promising results in image compressi...
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04/15/2022
Feature Compression for Rate Constrained Object Detection on the Edge
Recent advances in computer vision has led to a growth of interest in de...
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04/05/2022
Too Big to Fail? Active Few-Shot Learning Guided Logic Synthesis
Generating sub-optimal synthesis transformation sequences ("synthesis re...
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02/04/2022
Selective Network Linearization for Efficient Private Inference
Private inference (PI) enables inference directly on cryptographically s...
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11/04/2021
CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale
The privacy concerns of providing deep learning inference as a service h...
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10/27/2021
Millimeter Wave Wireless Assisted Robot Navigation with Link State Classification
The millimeter wave (mmWave) bands have attracted considerable attention...
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10/21/2021
OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis
Logic synthesis is a challenging and widely-researched combinatorial opt...
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07/20/2021
Single-Shot Compression for Hypothesis Testing
Enhanced processing power in the cloud allows constrained devices to off...
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06/17/2021
Sphynx: ReLU-Efficient Network Design for Private Inference
The emergence of deep learning has been accompanied by privacy concerns ...
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06/15/2021
Circa: Stochastic ReLUs for Private Deep Learning
The simultaneous rise of machine learning as a service and concerns over...
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05/20/2021
On the Optimization of Behavioral Logic Locking for High-Level Synthesis
The globalization of the electronics supply chain is requiring effective...
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03/12/2021
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Extracting interesting scenarios from real-world data as well as generat...
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03/02/2021
DeepReDuce: ReLU Reduction for Fast Private Inference
The recent rise of privacy concerns has led researchers to devise method...
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02/11/2021
On Graph Matching Using Generalized Seed Side-Information
In this paper, matching pairs of stocahstically generated graphs in the ...
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11/08/2020
Bait and Switch: Online Training Data Poisoning of Autonomous Driving Systems
We show that by controlling parts of a physical environment in which a p...
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11/04/2020
Detecting Backdoors in Neural Networks Using Novel Feature-Based Anomaly Detection
This paper proposes a new defense against neural network backdooring att...
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10/23/2020
On Evaluating Neural Network Backdoor Defenses
Deep neural networks (DNNs) demonstrate superior performance in various ...
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10/11/2020
ASSURE: RTL Locking Against an Untrusted Foundry
Semiconductor design companies are integrating proprietary intellectual ...
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09/19/2020
Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images
Unprecedented data collection and sharing have exacerbated privacy conce...
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08/30/2020
A Concentration of Measure Approach to Correlated Graph Matching
The graph matching problem emerges naturally in various applications suc...
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08/27/2020
Adversarially Robust Learning via Entropic Regularization
In this paper we propose a new family of algorithms for training adversa...
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06/15/2020
CryptoNAS: Private Inference on a ReLU Budget
Machine learning as a service has given raise to privacy concerns surrou...
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04/26/2020
Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors Against Backdooring Attacks
Deep learning (DL) offers potential improvements throughout the CAD tool...
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02/19/2020
NNoculation: Broad Spectrum and Targeted Treatment of Backdoored DNNs
This paper proposes a novel two-stage defense (NNoculation) against back...
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01/20/2020
On the Joint Typicality of Permutations of Sequences of Random Variables
Permutations of correlated sequences of random variables appear naturall...
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06/25/2019
Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection
There is substantial interest in the use of machine learning (ML) based ...
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12/04/2018
Outsourcing Private Machine Learning via Lightweight Secure Arithmetic Computation
In several settings of practical interest, two parties seek to collabora...
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11/05/2018
TrojanZero: Switching Activity-Aware Design of Undetectable Hardware Trojans with Zero Power and Area Footprint
Conventional Hardware Trojan (HT) detection techniques are based on the ...
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07/02/2018
FATE: Fast and Accurate Timing Error Prediction Framework for Low Power DNN Accelerator Design
Deep neural networks (DNN) are increasingly being accelerated on applica...
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05/30/2018
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks
Deep neural networks (DNNs) provide excellent performance across a wide ...
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02/11/2018
ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Neural Network Accelerators
Hardware accelerators are being increasingly deployed to boost the perfo...
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02/11/2018