Search Results for author:
Found 6 papers, 1 papers with code
TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding
Meta-Learning has emerged as a research direction to better transfer knowledge from related tasks to unseen but related tasks.
Not All Lotteries Are Made Equal
The Lottery Ticket Hypothesis (LTH) states that for a reasonably sized neural network, a sub-network within the same network yields no less performance than the dense counterpart when trained from the same initialization.
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning
In this work, we introduce AdaSplit which enables efficiently scaling SL to low resource scenarios by reducing bandwidth consumption and improving performance across heterogeneous clients.
Audiomer: A Convolutional Transformer For Keyword Spotting
Transformers have seen an unprecedented rise in Natural Language Processing and Computer Vision tasks.
Introducing Self-Attention to Target Attentive Graph Neural Networks
Session-based recommendation systems suggest relevant items to users by modeling user behavior and preferences using short-term anonymous sessions.
Ranked #5 on
Session-Based Recommendations
on yoochoose1/64
Rethinking Neural Networks With Benford's Law
To that end, we first define a metric, MLH (Model Enthalpy), that measures the closeness of a set of numbers to Benford's Law and we show empirically that it is a strong predictor of Validation Accuracy.
