7 papers
Scalable Batch Correction for Cell Painting via Batch-Dependent Kernels and Adaptive Sampling
Aditya Narayan Ravi, Snehal Vadvalkar, Abhishek Pandey +1
Cell Painting is a microscopy-based, high-content imaging assay that produces rich morphological profiles of cells and can support drug discovery by quantifying cellular responses…
Fundamental Limits of Non-Adaptive Group Testing with Markovian Correlation
Aditya Narayan Ravi, Ilan Shomorony
We study a correlated group testing model where items are infected according to a Markov chain, which creates bursty binfection patterns. Focusing on a very sparse infections regim…
Recovering a Message from an Incomplete Set of Noisy Fragments
Aditya Narayan Ravi, Alireza Vahid, Ilan Shomorony
We consider the problem of communicating over a channel that breaks the message block into fragments of random lengths, shuffles them out of order, and deletes a random fraction of…
Utilizing Free Clients in Federated Learning for Focused Model Enhancement
Aditya Narayan Ravi, Ilan Shomorony
Federated Learning (FL) is a distributed machine learning approach to learn models on decentralized heterogeneous data, without the need for clients to share their data. Many exist…
Coded Shotgun Sequencing
Aditya Narayan Ravi, Alireza Vahid, Ilan Shomorony
Most DNA sequencing technologies are based on the shotgun paradigm: many short reads are obtained from random unknown locations in the DNA sequence. A fundamental question, studied…
On the Capacity Enlargement of Gaussian Broadcast Channels with Passive Noisy Feedback
Aditya Narayan Ravi, Sibi Raj B. Pillai, Vinod Prabhakaran +1
It is well known that the capacity region of an average transmit power constrained Gaussian Broadcast Channel (GBC) with independent noise realizations at the receivers is enlarged…
Unreliable Multi-Armed Bandits: A Novel Approach to Recommendation Systems
Aditya Narayan Ravi, Pranav Poduval, Sharayu Moharir
We use a novel modification of Multi-Armed Bandits to create a new model for recommendation systems. We model the recommendation system as a bandit seeking to maximize reward by pu…