Search Results for author: Marc Pickett

Found 6 papers, 2 papers with code

CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions

1 code implementation14 Sep 2020 Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodriguez, Massimo Caccia, Qi She, Yu Chen, Quentin Jodelet, Ruiping Wang, Zheda Mai, David Vazquez, German I. Parisi, Nikhil Churamani, Marc Pickett, Issam Laradji, Davide Maltoni

In the last few years, we have witnessed a renewed and fast-growing interest in continual learning with deep neural networks with the shared objective of making current AI systems more adaptive, efficient and autonomous.

Benchmarking Continual Learning

A Brief Study of In-Domain Transfer and Learning from Fewer Samples using A Few Simple Priors

no code implementations13 Jul 2017 Marc Pickett, Ayush Sekhari, James Davidson

Domain knowledge can often be encoded in the structure of a network, such as convolutional layers for vision, which has been shown to increase generalization and decrease sample complexity, or the number of samples required for successful learning.

A Growing Long-term Episodic & Semantic Memory

no code implementations20 Oct 2016 Marc Pickett, Rami Al-Rfou, Louis Shao, Chris Tar

The long-term memory of most connectionist systems lies entirely in the weights of the system.

Transfer Learning

Conversational Contextual Cues: The Case of Personalization and History for Response Ranking

no code implementations1 Jun 2016 Rami Al-Rfou, Marc Pickett, Javier Snaider, Yun-Hsuan Sung, Brian Strope, Ray Kurzweil

Unlike previous efforts, which focused on modeling messages and responses, we extend the modeling to long context and participant's history.

Spontaneous Analogy by Piggybacking on a Perceptual System

no code implementations10 Oct 2013 Marc Pickett, David W. Aha

Using this representation, our system leverages perceptual algorithms to automatically create an ontology of relational structures and to efficiently retrieve analogs for new relational structures from long-term memory.

Retrieval

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