164 citations · 289 across the 19 of their papers we have counts for
20 papers
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
Florian Bordes, Shashank Shekhar, Mark Ibrahim +3
Synthetic image datasets offer unmatched advantages for designing and evaluating deep neural networks: they make it possible to (i) render as many data samples as needed, (ii) prec…
Multi-Task Learning Improves Performance In Deep Argument Mining Models
Amirhossein Farzam, Shashank Shekhar, Isaac Mehlhaff +1
The successful analysis of argumentative techniques from user-generated text is central to many downstream tasks such as political and market analysis. Recent argument mining tools…
Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations
Shashank Shekhar, Florian Bordes, Pascal Vincent +1
Joint-embedding based learning (e.g., SimCLR, MoCo, DINO) and reconstruction-based learning (e.g., BEiT, SimMIM, MAE) are the two leading paradigms for self-supervised learning of…
A Cookbook of Self-Supervised Learning
Randall Balestriero, Mark Ibrahim, Vlad Sobal +16
Self-supervised learning, dubbed the dark matter of intelligence, is a promising path to advance machine learning. Yet, much like cooking, training SSL methods is a delicate art wi…
UNet Based Pipeline for Lung Segmentation from Chest X-Ray Images
Shashank Shekhar, Ritika Nandi, H Srikanth Kamath
Biomedical image segmentation is one of the fastest growing fields which has seen extensive automation through the use of Artificial Intelligence. This has enabled widespread adopt…
Instantaneous Channel Oblivious Phase Shift Design for an IRS-Assisted SIMO System with Quantized Phase Shift
Shashank Shekhar, Athira Subhash, Tejesh Kella +1
We design the phase shifts of an intelligent reflecting surface (IRS)-assisted single-input-multiple-output communication system to minimize the outage probability (OP) and to maxi…
Robust Planning for Human-Robot Joint Tasks with Explicit Reasoning on Human Mental State
Anthony Favier, Shashank Shekhar, Rachid Alami
We consider the human-aware task planning problem where a human-robot team is given a shared task with a known objective to achieve. Recent approaches tackle it by modeling it as a…
Table Detection in the Wild: A Novel Diverse Table Detection Dataset and Method
Mrinal Haloi, Shashank Shekhar, Nikhil Fande +2
Recent deep learning approaches in table detection achieved outstanding performance and proved to be effective in identifying document layouts. Currently, available table detection…
SINR Analysis of an IRS Assisted MU-MISO System
Lakshmi Jayalal, Shashank Shekhar, Athira Subhash +1
In this work, we characterize the outage probability (OP) of an intelligent reflecting surface (IRS) assisted multi-user multiple-input-single-output (MU-MISO) communication system…
Software-defined Dynamic 5G Network Slice Management for Industrial Internet of Things
Ziran Min, Shashank Shekhar, Charif Mahmoudi +3
This paper addresses the challenges of delivering fine-grained Quality of Service (QoS) and communication determinism over 5G wireless networks for real-time and autonomous needs o…
Beyond neural scaling laws: beating power law scaling via data pruning
Ben Sorscher, Robert Geirhos, Shashank Shekhar +2
Widely observed neural scaling laws, in which error falls off as a power of the training set size, model size, or both, have driven substantial performance improvements in deep lea…
An Ensemble Model for Face Liveness Detection
Shashank Shekhar, Avinash Patel, Mrinal Haloi +1
In this paper, we present a passive method to detect face presentation attack a.k.a face liveness detection using an ensemble deep learning technique. Face liveness detection is on…
A Comparative study of Hyper-Parameter Optimization Tools
Shashank Shekhar, Adesh Bansode, Asif Salim
Most of the machine learning models have associated hyper-parameters along with their parameters. While the algorithm gives the solution for parameters, its utility for model perfo…
Joint Power-control and Antenna Selection in User-Centric Cell-Free Systems with Mixed Resolution ADC
Shashank Shekhar, Athira Subhash, Muralikrishnan Srinivasan +1
In this paper, we propose a scheme for the joint optimization of the user transmit power and the antenna selection at the access points (AP)s of a user-centric cell-free massive mu…
Peer-to-Peer Communication Trade-Offs for Smart Grid Applications
Purboday Ghosh, Shashank Shekhar, Yashen Lin +2
Virtual topologies in peer-to-peer networks can reduce the traffic consumed by altering the logical connectivity of peers without altering the underlying network. However, such spa…
Outage Probability Analysis of Uplink Cell-Free Massive MIMO Network with and without Pilot Contamination
Shashank Shekhar, Muralikrishnan Srinivasan, Sheetal Kalyani +1
This paper derives approximate outage probability (OP) expressions for uplink cell-free massive multiple-input-multiple-output (CF-mMIMO) systems with and without pilot contaminati…
FECBench: A Holistic Interference-aware Approach for Application Performance Modeling
Yogesh D. Barve, Shashank Shekhar, Ajay Dev Chhokra +5
Services hosted in multi-tenant cloud platforms often encounter performance interference due to contention for non-partitionable resources, which in turn causes unpredictable behav…
Road Damage Detection And Classification In Smartphone Captured Images Using Mask R-CNN
Janpreet Singh, Shashank Shekhar
This paper summarizes the design, experiments and results of our solution to the Road Damage Detection and Classification Challenge held as part of the 2018 IEEE International Conf…
Learning and Tuning Meta-heuristics in Plan Space Planning
Shashank Shekhar, Deepak Khemani
In recent years, the planning community has observed that techniques for learning heuristic functions have yielded improvements in performance. One approach is to use offline learn…
Flare: Architecture for rapid and easy development of Internet-based Applications
Shashank Shekhar, Mohit Soni, NVSN Kalyan Chakravarthy
We propose an architecture, Flare, that is a structured and easy way to develop applications rapidly, in a multitude of languages, which make use of online storage of data and mana…