b'Kaushik Roy'

research

∙ 09/11/2023

Hi Model, generating 'nice' instead of 'good' is not as bad as generating 'rice'! Towards Context and Semantic Infused Dialogue Generation Loss Function and Evaluation Metric

Over the past two decades, dialogue modeling has made significant stride...

0 Abhisek Tiwari, et al. ∙

research

∙ 07/31/2023

L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space

The performance of a lifelong learning (L3) model degrades when it is tr...

0 Kaushik Roy, et al. ∙

research

∙ 07/31/2023

Subspace Distillation for Continual Learning

An ultimate objective in continual learning is to preserve knowledge lea...

0 Kaushik Roy, et al. ∙

research

∙ 07/21/2023

EV-Planner: Energy-Efficient Robot Navigation via Event-Based Physics-Guided Neuromorphic Planner

Vision-based object tracking is an essential precursor to performing aut...

0 Sourav Sanyal, et al. ∙

research

∙ 07/11/2023

Memorization Through the Lens of Curvature of Loss Function Around Samples

Neural networks are overparametrized and easily overfit the datasets the...

0 Isha Garg, et al. ∙

research

∙ 06/27/2023

S-TLLR: STDP-inspired Temporal Local Learning Rule for Spiking Neural Networks

Spiking Neural Networks (SNNs) are biologically plausible models that ha...

0 Marco Paul E. Apolinario, et al. ∙

research

∙ 06/24/2023

IERL: Interpretable Ensemble Representation Learning – Combining CrowdSourced Knowledge and Distributed Semantic Representations

Large Language Models (LLMs) encode meanings of words in the form of dis...

0 Yuxin Zi, et al. ∙

research

∙ 06/23/2023

Knowledge-Infused Self Attention Transformers

Transformer-based language models have achieved impressive success in va...

0 Kaushik Roy, et al. ∙

research

∙ 06/16/2023

Process Knowledge-infused Learning for Clinician-friendly Explanations

Language models have the potential to assess mental health using social ...

0 Kaushik Roy, et al. ∙

research

∙ 06/05/2023

Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation

Event-based cameras offer a low-power alternative to frame-based cameras...

0 Shubham Negi, et al. ∙

research

∙ 06/01/2023

Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes

As people become more aware of their food choices, food computation mode...

0 Revathy Venkataramanan, et al. ∙

research

∙ 05/22/2023

FEDORA: Flying Event Dataset fOr Reactive behAvior

The ability of living organisms to perform complex high speed manoeuvers...

0 Amogh Joshi, et al. ∙

research

∙ 05/13/2023

ProKnow: Process Knowledge for Safety Constrained and Explainable Question Generation for Mental Health Diagnostic Assistance

Current Virtual Mental Health Assistants (VMHAs) provide counseling and ...

0 Kaushik Roy, et al. ∙

research

∙ 05/08/2023

Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust

A fundamental question in natural language processing is - what kind of ...

0 Kaushik Roy, et al. ∙

research

∙ 05/08/2023

Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data

Decentralized learning enables the training of deep learning models over...

0 Sai Aparna Aketi, et al. ∙

research

∙ 05/01/2023

Neurosymbolic AI - Why, What, and How

Humans interact with the environment using a combination of perception -...

0 Amit Sheth, et al. ∙

research

∙ 04/14/2023

Fairness in Visual Clustering: A Novel Transformer Clustering Approach

Promoting fairness for deep clustering models in unsupervised clustering...

0 Xuan-Bac Nguyen, et al. ∙

research

∙ 04/09/2023

Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning

Decentralized learning enables serverless training of deep neural networ...

0 Deepak Ravikumar, et al. ∙

research

∙ 03/31/2023

Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance for Telehealth: The Mental Health Case

After the pandemic, artificial intelligence (AI) powered support for men...

0 Kaushik Roy, et al. ∙

research

∙ 03/27/2023

CoDeC: Communication-Efficient Decentralized Continual Learning

Training at the edge utilizes continuously evolving data generated at di...

0 Sakshi Choudhary, et al. ∙

research

∙ 03/13/2023

X-Former: In-Memory Acceleration of Transformers

Transformers have achieved great success in a wide variety of natural la...

0 Shrihari Sridharan, et al. ∙

research

∙ 02/03/2023

HADES: Hardware/Algorithm Co-design in DNN accelerators using Energy-efficient Approximate Alphabet Set Multipliers

Edge computing must be capable of executing computationally intensive al...

0 Arani Roy, et al. ∙

research

∙ 02/02/2023

Continual Learning with Scaled Gradient Projection

In neural networks, continual learning results in gradient interference ...

0 Gobinda Saha, et al. ∙

research

∙ 12/09/2022

A Comparative Performance Analysis of Explainable Machine Learning Models With And Without RFECV Feature Selection Technique Towards Ransomware Classification

Ransomware has emerged as one of the major global threats in recent days...

0 Rawshan Ara Mowri, et al. ∙

research

∙ 11/19/2022

HALSIE - Hybrid Approach to Learning Segmentation by Simultaneously Exploiting Image and Event Modalities

Standard frame-based algorithms fail to retrieve accurate segmentation m...

0 Shristi Das Biswas, et al. ∙

research

∙ 11/03/2022

Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks

Spiking Neural Networks (SNNs) are bio-plausible models that hold great ...

0 Marco Paul E. Apolinario, et al. ∙

research

∙ 10/16/2022

Interpretable Machine Learning for Detection and Classification of Ransomware Families Based on API Calls

Ransomware has appeared as one of the major global threats in recent day...

0 Rawshan Ara Mowri, et al. ∙

research

∙ 10/09/2022

KSAT: Knowledge-infused Self Attention Transformer – Integrating Multiple Domain-Specific Contexts

Domain-specific language understanding requires integrating multiple pie...

37 Kaushik Roy, et al. ∙

research

∙ 10/03/2022

Event-based Temporally Dense Optical Flow Estimation with Sequential Neural Networks

Prior works on event-based optical flow estimation have investigated sev...

0 Wachirawit Ponghiran, et al. ∙

research

∙ 10/03/2022

DOTIE – Detecting Objects through Temporal Isolation of Events using a Spiking Architecture

Vision-based autonomous navigation systems rely on fast and accurate obj...

0 Manish Nagaraj, et al. ∙

research

∙ 09/28/2022

Neighborhood Gradient Clustering: An Efficient Decentralized Learning Method for Non-IID Data Distributions

Decentralized learning over distributed datasets can have significantly ...

0 Sai Aparna Aketi, et al. ∙

research

∙ 09/21/2022

Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics

Event-based cameras have recently shown great potential for high-speed m...

0 Adarsh Kumar Kosta, et al. ∙

research

∙ 09/19/2022

RAMP-Net: A Robust Adaptive MPC for Quadrotors via Physics-informed Neural Network

Model Predictive Control (MPC) is a state-of-the-art (SOTA) control tech...

0 Sourav Sanyal, et al. ∙

research

∙ 06/18/2022

Can Language Models Capture Graph Semantics? From Graphs to Language Model and Vice-Versa

Knowledge Graphs are a great resource to capture semantic knowledge in t...

4 Tarun Garg, et al. ∙

research

∙ 06/03/2022

A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks

Deep Learning neural networks are pervasive, but traditional computer ar...

0 Wilfried Haensch, et al. ∙

research

∙ 05/27/2022

Learning to Automate Follow-up Question Generation using Process Knowledge for Depression Triage on Reddit Posts

Conversational Agents (CAs) powered with deep language models (DLMs) hav...

19 Shrey Gupta, et al. ∙

research

∙ 05/06/2022

Norm-Scaling for Out-of-Distribution Detection

Out-of-Distribution (OoD) inputs are examples that do not belong to the ...

0 Deepak Ravikumar, et al. ∙

research

∙ 04/26/2022

Process Knowledge-infused Learning for Suicidality Assessment on Social Media

Improving the performance and natural language explanations of deep lear...

37 Kaushik Roy, et al. ∙

research

∙ 03/25/2022

Cryogenic Neuromorphic Hardware

The revolution in artificial intelligence (AI) brings up an enormous sto...

0 Md Mazharul Islam, et al. ∙

research

∙ 01/21/2022

TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data

Advances in Federated Learning and an abundance of user data have enable...

0 Isha Garg, et al. ∙

research

∙ 12/20/2021

Encoding Hierarchical Information in Neural Networks helps in Subpopulation Shift

Over the past decade, deep neural networks have proven to be adept in im...

0 Amitangshu Mukherjee, et al. ∙

research

∙ 11/17/2021

L4-Norm Weight Adjustments for Converted Spiking Neural Networks

Spiking Neural Networks (SNNs) are being explored for their potential en...

0 Jason Allred, et al. ∙

research

∙ 11/17/2021

Low Precision Decentralized Distributed Training over IID and non-IID Data

Decentralized distributed learning is the key to enabling large-scale ma...

0 Sai Aparna Aketi, et al. ∙

research

∙ 10/18/2021

BERMo: What can BERT learn from ELMo?

We propose BERMo, an architectural modification to BERT, which makes pre...

0 Sangamesh Kodge, et al. ∙

research

∙ 10/01/2021

One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency

Spiking Neural Networks (SNNs) are energy efficient alternatives to comm...

0 Sayeed Shafayet Chowdhury, et al. ∙

research

∙ 09/19/2021

On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars

Applications based on Deep Neural Networks (DNNs) have grown exponential...

6 Deboleena Roy, et al. ∙

research

∙ 09/16/2021

RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning

Present-day Deep Reinforcement Learning (RL) systems show great promise ...

21 Adarsh Kumar Kosta, et al. ∙

research

∙ 09/14/2021

Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing

Tremendous progress has been made in sequential processing with the rece...

0 Bing Han, et al. ∙

research

∙ 09/14/2021

Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems

The ubiquitous use of IoT and machine learning applications is creating ...

0 Yinghan Long, et al. ∙

research

∙ 09/10/2021

Saliency Guided Experience Packing for Replay in Continual Learning

Artificial learning systems aspire to mimic human intelligence by contin...

0 Gobinda Saha, et al. ∙

Kaushik Roy

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