Radu Marculescu | DeepAI

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Featured Co-authors

Wei Chen
304 publications
Janardhan Rao Doppa
41 publications
Diana Marculescu
37 publications
Umang Bhatt
29 publications
Umit Y. Ogras
23 publications
Ali Akoglu
16 publications
Kartikeya Bhardwaj
14 publications
Sumit K. Mandal
12 publications
Partha Pratim Pande
11 publications
Brian Davis
11 publications
Joshua Mack
11 publications

∙ 05/13/2023

TIPS: Topologically Important Path Sampling for Anytime Neural Networks

Anytime neural networks (AnytimeNNs) are a promising solution to adaptiv...

0 Guihong Li, et al. ∙

∙ 03/29/2023

Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation

Transformers have shown great success in medical image segmentation. How...

0 Md Mostafijur Rahman, et al. ∙

∙ 01/26/2023

ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients

Neural Architecture Search (NAS) is widely used to automatically design ...

0 Guihong Li, et al. ∙

∙ 01/01/2023

Efficient On-device Training via Gradient Filtering

Despite its importance for federated learning, continuous learning and m...

0 Yuedong Yang, et al. ∙

∙ 03/31/2022

Dynamic Multimodal Fusion

Deep multimodal learning has achieved great progress in recent years. Ho...

0 Zihui Xue, et al. ∙

∙ 01/31/2022

SUGAR: Efficient Subgraph-level Training via Resource-aware Graph Partitioning

Graph Neural Networks (GNNs) have demonstrated a great potential in a va...

0 Zihui Xue, et al. ∙

∙ 09/22/2021

DAS: Dynamic Adaptive Scheduling for Energy-Efficient Heterogeneous SoCs

Domain-specific systems-on-chip (DSSoCs) aim at bridging the gap between...

0 A. Alper Goksoy, et al. ∙

∙ 08/01/2021

FLASH: Fast Neural Architecture Search with Hardware Optimization

Neural architecture search (NAS) is a promising technique to design effi...

0 Guihong Li, et al. ∙

∙ 08/25/2020

New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design

In this paper, we first highlight three major challenges to large-scale ...

8 Kartikeya Bhardwaj, et al. ∙

∙ 07/18/2020

Runtime Task Scheduling using Imitation Learning for Heterogeneous Many-Core Systems

Domain-specific systems-on-chip, a class of heterogeneous many-core syst...

0 Anish Krishnakumar, et al. ∙

∙ 04/08/2020

Centralized and decentralized isolation strategies and their impact on the COVID-19 pandemic dynamics

The infectious diseases are spreading due to human interactions enabled ...

0 Alexandru Topirceanu, et al. ∙

∙ 04/07/2020

FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning

In this paper, we identify a new phenomenon called activation-divergence...

8 Wei Chen, et al. ∙

∙ 03/19/2020

DS3: A System-Level Domain-Specific System-on-Chip Simulation Framework

Heterogeneous systems-on-chip (SoCs) are highly favorable computing plat...

0 Samet E. Arda, et al. ∙

∙ 10/23/2019

EdgeAI: A Vision for Deep Learning in IoT Era

The significant computational requirements of deep learning present a ma...

49 Kartikeya Bhardwaj, et al. ∙

∙ 10/02/2019

Towards Unifying Neural Architecture Space Exploration and Generalization

In this paper, we address a fundamental research question of significant...

0 Kartikeya Bhardwaj, et al. ∙

∙ 08/10/2019

Work-in-Progress: A Simulation Framework for Domain-Specific System-on-Chips

Heterogeneous system-on-chips (SoCs) have become the standard embedded c...

0 Samet E. Arda, et al. ∙

∙ 07/26/2019

Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT

Model compression has emerged as an important area of research for deplo...

4 Kartikeya Bhardwaj, et al. ∙

∙ 05/17/2019

Dream Distillation: A Data-Independent Model Compression Framework

Model compression is eminently suited for deploying deep learning on IoT...

5 Kartikeya Bhardwaj, et al. ∙

∙ 01/20/2019

NIF: A Framework for Quantifying Neural Information Flow in Deep Networks

In this paper, we present a new approach to interpreting deep learning m...

0 Brian Davis, et al. ∙

∙ 12/06/2018

Climate Anomalies vs Air Pollution: Carbon Emissions and Anomaly Networks

This project aims to shed light on how man-made carbon emissions are aff...

0 Anshul Goyal, et al. ∙

∙ 12/01/2018

A Dynamic Network and Representation LearningApproach for Quantifying Economic Growth fromSatellite Imagery

Quantifying the improvement in human living standard, as well as the cit...

0 Jiqian Dong, et al. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙