H. T. Kung | DeepAI

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Featured Co-authors

Ang Li
165 publications
Meng Li
72 publications
Xin Dong
23 publications
Youngjune Gwon
13 publications
Sai Qian Zhang
11 publications
Bradley McDanel
10 publications
Junfeng Guo
10 publications
Zhongnan Qu
9 publications
Miriam Cha
8 publications
Ziyun Li
7 publications
Surat Teerapittayanon
7 publications

∙ 01/05/2023

StitchNet: Composing Neural Networks from Pre-Trained Fragments

We propose StitchNet, a novel neural network creation paradigm that stit...

0 Surat Teerapittayanon, et al. ∙

∙ 07/19/2022

SphereFed: Hyperspherical Federated Learning

Federated Learning aims at training a global model from multiple decentr...

2 Xin Dong, et al. ∙

∙ 04/10/2022

SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems

We design deep neural networks (DNNs) and corresponding networks' splitt...

1 Xin Dong, et al. ∙

∙ 10/28/2021

FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding

Block Floating Point (BFP) can efficiently support quantization for Deep...

12 Sai Qian Zhang, et al. ∙

∙ 04/23/2021

Lightweight Detection of Out-of-Distribution and Adversarial Samples via Channel Mean Discrepancy

Detecting out-of-distribution (OOD) and adversarial samples is essential...

6 Xin Dong, et al. ∙

∙ 07/13/2020

Term Revealing: Furthering Quantization at Run Time on Quantized DNNs

We present a novel technique, called Term Revealing (TR), for furthering...

0 H. T. Kung, et al. ∙

∙ 07/19/2019

DaiMoN: A Decentralized Artificial Intelligence Model Network

We introduce DaiMoN, a decentralized artificial intelligence model netwo...

1 Surat Teerapittayanon, et al. ∙

∙ 06/17/2019

CheckNet: Secure Inference on Untrusted Devices

We introduce CheckNet, a method for secure inference with deep neural ne...

5 Marcus Comiter, et al. ∙

∙ 05/01/2019

Full-stack Optimization for Accelerating CNNs with FPGA Validation

We present a full-stack optimization framework for accelerating inferenc...

0 Bradley McDanel, et al. ∙

∙ 12/12/2018

Adversarial Learning of Semantic Relevance in Text to Image Synthesis

We describe a new approach that improves the training of generative adve...

0 Miriam Cha, et al. ∙

∙ 11/07/2018

Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization

This paper describes a novel approach of packing sparse convolutional ne...

0 H. T. Kung, et al. ∙

∙ 02/09/2018

InferBeam: A Fast Beam Alignment Protocol for Millimeter-wave Networking

We introduce fast millimeter-wave base station (BS) and its antenna sect...

0 Sai Qian Zhang, et al. ∙

∙ 10/21/2017

Incomplete Dot Products for Dynamic Computation Scaling in Neural Network Inference

We propose the use of incomplete dot products (IDP) to dynamically adjus...

0 Bradley McDanel, et al. ∙

∙ 09/06/2017

Embedded Binarized Neural Networks

We study embedded Binarized Neural Networks (eBNNs) with the aim of allo...

0 Bradley McDanel, et al. ∙

∙ 09/06/2017

BranchyNet: Fast Inference via Early Exiting from Deep Neural Networks

Deep neural networks are state of the art methods for many learning task...

0 Surat Teerapittayanon, et al. ∙

∙ 09/06/2017

Distributed Deep Neural Networks over the Cloud, the Edge and End Devices

We propose distributed deep neural networks (DDNNs) over distributed com...

0 Surat Teerapittayanon, et al. ∙

∙ 09/05/2017

Language Modeling by Clustering with Word Embeddings for Text Readability Assessment

We present a clustering-based language model using word embeddings for t...

0 Miriam Cha, et al. ∙

∙ 11/19/2015

Multimodal sparse representation learning and applications

Unsupervised methods have proven effective for discriminative tasks in a...

0 Miriam Cha, et al. ∙