188 citations · 271 across the 15 of their papers we have counts for
15 papers
Cross-modal Learning for Multi-modal Video Categorization
Palash Goyal, Saurabh Sahu, Shalini Ghosh +1
Multi-modal machine learning (ML) models can process data in multiple modalities (e.g., video, audio, text) and are useful for video content analysis in a variety of problems (e.g.…
Exploiting Temporal Coherence for Multi-modal Video Categorization
Palash Goyal, Saurabh Sahu, Shalini Ghosh +1
Multimodal ML models can process data in multiple modalities (e.g., video, images, audio, text) and are useful for video content analysis in a variety of problems (e.g., object det…
RILOD: Near Real-Time Incremental Learning for Object Detection at the Edge
Dawei Li, Serafettin Tasci, Shalini Ghosh +3
Object detection models shipped with camera-equipped edge devices cannot cover the objects of interest for every user. Therefore, the incremental learning capability is a critical…
Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML
Jie Zhang, Junting Zhang, Shalini Ghosh +4
Lifelong learning, the problem of continual learning where tasks arrive in sequence, has been lately attracting more attention in the computer vision community. The aim of lifelong…
Class-incremental Learning via Deep Model Consolidation
Junting Zhang, Jie Zhang, Shalini Ghosh +5
Deep neural networks (DNNs) often suffer from "catastrophic forgetting" during incremental learning (IL) --- an abrupt degradation of performance on the original set of classes whe…
Generating Natural Language Explanations for Visual Question Answering using Scene Graphs and Visual Attention
Shalini Ghosh, Giedrius Burachas, Arijit Ray +1
In this paper, we present a novel approach for the task of eXplainable Question Answering (XQA), i.e., generating natural language (NL) explanations for the Visual Question Answeri…
MICIK: MIning Cross-Layer Inherent Similarity Knowledge for Deep Model Compression
Jie Zhang, Xiaolong Wang, Dawei Li +3
State-of-the-art deep model compression methods exploit the low-rank approximation and sparsity pruning to remove redundant parameters from a learned hidden layer. However, they pr…
Generative Visual Dialogue System via Adaptive Reasoning and Weighted Likelihood Estimation
Heming Zhang, Shalini Ghosh, Larry Heck +4
The key challenge of generative Visual Dialogue (VD) systems is to respond to human queries with informative answers in natural and contiguous conversation flow. Traditional Maximu…
Data Masking with Privacy Guarantees
Anh T. Pham, Shalini Ghosh, Vinod Yegneswaran
We study the problem of data release with privacy, where data is made available with privacy guarantees while keeping the usability of the data as high as possible --- this is impo…
Time Series Deinterleaving of DNS Traffic
Amir Asiaee, Hardik Goel, Shalini Ghosh +2
Stream deinterleaving is an important problem with various applications in the cybersecurity domain. In this paper, we consider the specific problem of deinterleaving DNS data stre…
Trusted Neural Networks for Safety-Constrained Autonomous Control
Shalini Ghosh, Amaury Mercier, Dheeraj Pichapati +3
We propose Trusted Neural Network (TNN) models, which are deep neural network models that satisfy safety constraints critical to the application domain. We investigate different me…
A Unified Framework for Domain Adaptation using Metric Learning on Manifolds
Sridhar Mahadevan, Bamdev Mishra, Shalini Ghosh
We present a novel framework for domain adaptation, whereby both geometric and statistical differences between a labeled source domain and unlabeled target domain can be integrated…
Contextual LSTM (CLSTM) models for Large scale NLP tasks
Shalini Ghosh, Oriol Vinyals, Brian Strope +3
Documents exhibit sequential structure at multiple levels of abstraction (e.g., sentences, paragraphs, sections). These abstractions constitute a natural hierarchy for representing…
Virus Detection in Multiplexed Nanowire Arrays using Hidden Semi-Markov models
Shalini Ghosh, Patrick Lincoln, Christian Petersen +1
In this paper, we address the problem of real-time detection of viruses docking to nanowires, especially when multiple viruses dock to the same nano-wire. The task becomes more com…
ARSENAL: Automatic Requirements Specification Extraction from Natural Language
Shalini Ghosh, Daniel Elenius, Wenchao Li +3
Requirements are informal and semi-formal descriptions of the expected behavior of a complex system from the viewpoints of its stakeholders (customers, users, operators, designers,…