research
∙
07/08/2023
Rosko: Row Skipping Outer Products for Sparse Matrix Multiplication Kernels
We propose Rosko – row skipping outer products – for deriving sparse mat...
share
research
∙
04/12/2023
MEMA Runtime Framework: Minimizing External Memory Accesses for TinyML on Microcontrollers
We present the MEMA framework for the easy and quick derivation of effic...
research
∙
01/05/2023
StitchNet: Composing Neural Networks from Pre-Trained Fragments
We propose StitchNet, a novel neural network creation paradigm that stit...
research
∙
07/19/2022
SphereFed: Hyperspherical Federated Learning
Federated Learning aims at training a global model from multiple decentr...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
07/13/2020
Term Revealing: Furthering Quantization at Run Time on Quantized DNNs
We present a novel technique, called Term Revealing (TR), for furthering...
research
∙
07/19/2019
DaiMoN: A Decentralized Artificial Intelligence Model Network
We introduce DaiMoN, a decentralized artificial intelligence model netwo...
research
∙
06/17/2019
CheckNet: Secure Inference on Untrusted Devices
We introduce CheckNet, a method for secure inference with deep neural ne...
research
∙
05/01/2019
Full-stack Optimization for Accelerating CNNs with FPGA Validation
We present a full-stack optimization framework for accelerating inferenc...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
09/06/2017
Embedded Binarized Neural Networks
We study embedded Binarized Neural Networks (eBNNs) with the aim of allo...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
11/19/2015
