26 citations · 181 across the 49 of their papers we have counts for
15 papers · 1 filter
Encoding Hierarchical Information in Neural Networks helps in Subpopulation Shift
Amitangshu Mukherjee, Isha Garg, Kaushik Roy
Over the past decade, deep neural networks have proven to be adept in image classification tasks, often surpassing humans in terms of accuracy. However, standard neural networks of…
L4-Norm Weight Adjustments for Converted Spiking Neural Networks
Jason Allred, Kaushik Roy
Spiking Neural Networks (SNNs) are being explored for their potential energy efficiency benefits due to sparse, event-driven computation. Non-spiking artificial neural networks are…
Low Precision Decentralized Distributed Training over IID and non-IID Data
Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy
Decentralized distributed learning is the key to enabling large-scale machine learning (training) on edge devices utilizing private user-generated local data, without relying on th…
BERMo: What can BERT learn from ELMo?
Sangamesh Kodge, Kaushik Roy
We propose BERMo, an architectural modification to BERT, which makes predictions based on a hierarchy of surface, syntactic and semantic language features. We use linear combinatio…
RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning
Adarsh Kumar Kosta, Malik Aqeel Anwar, Priyadarshini Panda +2
Present-day Deep Reinforcement Learning (RL) systems show great promise towards building intelligent agents surpassing human-level performance. However, the computational complexit…
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems
Yinghan Long, Indranil Chakraborty, Gopalakrishnan Srinivasan +1
The ubiquitous use of IoT and machine learning applications is creating large amounts of data that require accurate and real-time processing. Although edge-based smart data process…
On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars
Chun Tao, Deboleena Roy, Indranil Chakraborty +1
Applications based on Deep Neural Networks (DNNs) have grown exponentially in the past decade. To match their increasing computational needs, several Non-Volatile Memory (NVM) cros…
Saliency Guided Experience Packing for Replay in Continual Learning
Gobinda Saha, Kaushik Roy
Artificial learning systems aspire to mimic human intelligence by continually learning from a stream of tasks without forgetting past knowledge. One way to enable such learning is…
Knowledge-intensive Language Understanding for Explainable AI
Amit Sheth, Manas Gaur, Kaushik Roy +1
AI systems have seen significant adoption in various domains. At the same time, further adoption in some domains is hindered by inability to fully trust an AI system that it will n…
Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits
Kaushik Roy, Qi Zhang, Manas Gaur +1
Contextual Bandits find important use cases in various real-life scenarios such as online advertising, recommendation systems, healthcare, etc. However, most of the algorithms use…
NLP is Not enough -- Contextualization of User Input in Chatbots
Nathan Dolbir, Triyasha Dastidar, Kaushik Roy
AI chatbots have made vast strides in technology improvement in recent years and are already operational in many industries. Advanced Natural Language Processing techniques, based…
"Who can help me?": Knowledge Infused Matching of Support Seekers and Support Providers during COVID-19 on Reddit
Manas Gaur, Kaushik Roy, Aditya Sharma +2
During the ongoing COVID-19 crisis, subreddits on Reddit, such as r/Coronavirus saw a rapid growth in user's requests for help (support seekers - SSs) including individuals with va…
eDarkTrends: Harnessing Social Media Trends in Substance use disorders for Opioid Listings on Cryptomarket
Usha Lokala, Francois Lamy, Triyasha Ghosh Dastidar +4
Opioid and substance misuse is rampant in the United States today, with the phenomenon known as the opioid crisis. The relationship between substance use and mental health has been…
Knowledge Infused Policy Gradients for Adaptive Pandemic Control
Kaushik Roy, Qi Zhang, Manas Gaur +1
COVID-19 has impacted nations differently based on their policy implementations. The effective policy requires taking into account public information and adaptability to new knowle…
"Is depression related to cannabis?": A knowledge-infused model for Entity and Relation Extraction with Limited Supervision
Kaushik Roy, Usha Lokala, Vedant Khandelwal +1
With strong marketing advocacy of the benefits of cannabis use for improved mental health, cannabis legalization is a priority among legislators. However, preliminary scientific re…