33 citations · 57 across the 6 of their papers we have counts for
8 papers
Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier
Arkabandhu Chowdhury, Mingchao Jiang, Swarat Chaudhuri +1
Recent papers have suggested that transfer learning can outperform sophisticated meta-learning methods for few-shot image classification. We take this hypothesis to its logical con…
Meta-Meta Classification for One-Shot Learning
Arkabandhu Chowdhury, Dipak Chaudhari, Swarat Chaudhuri +1
We present a new approach, called meta-meta classification, to learning in small-data settings. In this approach, one uses a large set of learning problems to design an ensemble of…
Searching a Database of Source Codes Using Contextualized Code Search
Rohan Mukherjee, Swarat Chaudhuri, Chris Jermaine
Consider the case where a programmer has written some part of a program, but has left part of the program (such as a method or a function body) incomplete. The goal is to use the c…
Declarative Recursive Computation on an RDBMS, or, Why You Should Use a Database For Distributed Machine Learning
Dimitrije Jankov, Shangyu Luo, Binhang Yuan +4
A number of popular systems, most notably Google's TensorFlow, have been implemented from the ground up to support machine learning tasks. We consider how to make a very small set…
Pangea: Monolithic Distributed Storage for Data Analytics
Jia Zou, Arun Iyengar, Chris Jermaine
Storage and memory systems for modern data analytics are heavily layered, managing shared persistent data, cached data, and non-shared execution data in separate systems such as di…
PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development
Jia Zou, R. Matthew Barnett, Tania Lorido-Botran +6
This paper describes PlinyCompute, a system for development of high-performance, data-intensive, distributed computing tools and libraries. In the large, PlinyCompute presents the…