no code implementations • 18 Jun 2021 • Sauptik Dhar, Javad Heydari, Samarth Tripathi, Unmesh Kurup, Mohak Shah
Limited availability of labeled-data makes any supervised learning problem challenging.
no code implementations • 8 May 2020 • Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
With the general trend of increasing Convolutional Neural Network (CNN) model sizes, model compression and acceleration techniques have become critical for the deployment of these models on edge devices.
1 code implementation • 6 Nov 2019 • Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
Tuning machine learning models at scale, especially finding the right hyperparameter values, can be difficult and time-consuming.
no code implementations • 2 Nov 2019 • Sauptik Dhar, Junyao Guo, Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
However, on-device learning is an expansive field with connections to a large number of related topics in AI and machine learning (including online learning, model adaptation, one/few-shot learning, etc.).
no code implementations • 14 May 2019 • Samarth Tripathi, Jiayi Liu, Unmesh Kurup, Mohak Shah, Sauptik Dhar
In this paper, we explore techniques centered around periodic sampling of model weights that provide convergence improvements on gradient update methods (vanilla \acs{SGD}, Momentum, Adam) for a variety of vision problems (classification, detection, segmentation).
no code implementations • cs.AI 2018 • Samarth Tripathi, Homayoon Beigi
Emotion recognition has become an important field of re- search in Human Computer Interactions and there is a grow- ing need for automatic emotion recognition systems.
no code implementations • 2 Jul 2018 • Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
We perform a variety of analysis using the MNIST dataset and validate the approach with a number of DNN models using pre-trained models on the ImageNet dataset.
no code implementations • 30 Apr 2018 • Samarth Tripathi, Renbo Tu
In this paper, we present the result of adopting skip connections and dense layers, previously used in image classification tasks, in the Fisher GAN implementation.
2 code implementations • 16 Apr 2018 • Samarth Tripathi, Sarthak Tripathi, Homayoon Beigi
Emotion recognition has become an important field of research in Human Computer Interactions as we improve upon the techniques for modelling the various aspects of behaviour.