activity
20162019
most citedTransfer Learning in Visual and Relational Reasoning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV20191 cited

Transfer Learning in Visual and Relational Reasoning

T. S. Jayram, Vincent Marois, Tomasz Kornuta +3

Transfer learning has become the de facto standard in computer vision and natural language processing, especially where labeled data is scarce. Accuracy can be significantly improv…

cs.CV2018

On transfer learning using a MAC model variant

Vincent Marois, T. S. Jayram, Vincent Albouy +3

We introduce a variant of the MAC model (Hudson and Manning, ICLR 2018) with a simplified set of equations that achieves comparable accuracy, while training faster. We evaluate bot…

cs.LG2018

Learning to Remember, Forget and Ignore using Attention Control in Memory

T. S. Jayram, Younes Bouhadjar, Ryan L. McAvoy +4

Typical neural networks with external memory do not effectively separate capacity for episodic and working memory as is required for reasoning in humans. Applying knowledge gained…

cs.LG2018

Using Multi-task and Transfer Learning to Solve Working Memory Tasks

T. S. Jayram, Tomasz Kornuta, Ryan L. McAvoy +1

We propose a new architecture called Memory-Augmented Encoder-Solver (MAES) that enables transfer learning to solve complex working memory tasks adapted from cognitive psychology.…

cs.CC2017

Resource-Efficient Common Randomness and Secret-Key Schemes

Badih Ghazi, T. S. Jayram

We study common randomness where two parties have access to i.i.d. samples from a known random source, and wish to generate a shared random key using limited (or no) communication…

cs.IT2016

A note on some inequalities used in channel polarization and polar coding

T. S. Jayram, Erdal Arikan

We give a unified treatment of some inequalities that are used in the proofs of channel polarization theorems involving a binary-input discrete memoryless channel.