47 citations · 115 across the 14 of their papers we have counts for
5 papers · 1 filter
Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
Yuxin Tang, Zhimin Ding, Dimitrije Jankov +3
The relational data model was designed to facilitate large-scale data management and analytics. We consider the problem of how to differentiate computations expressed relationally.…
LOFT: Finding Lottery Tickets through Filter-wise Training
Qihan Wang, Chen Dun, Fangshuo Liao +2
Recent work on the Lottery Ticket Hypothesis (LTH) shows that there exist ``\textit{winning tickets}'' in large neural networks. These tickets represent ``sparse'' versions of the…
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout
Chen Dun, Mirian Hipolito, Chris Jermaine +2
Asynchronous learning protocols have regained attention lately, especially in the Federated Learning (FL) setup, where slower clients can severely impede the learning process. Here…
Neural Program Generation Modulo Static Analysis
Rohan Mukherjee, Yeming Wen, Dipak Chaudhari +3
State-of-the-art neural models of source code tend to be evaluated on the generation of individual expressions and lines of code, and commonly fail on long-horizon tasks such as th…
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…