6 citations · 14 across the 3 of their papers we have counts for
6 papers
Iterative Data Programming for Expanding Text Classification Corpora
Neil Mallinar, Abhishek Shah, Tin Kam Ho +2
Real-world text classification tasks often require many labeled training examples that are expensive to obtain. Recent advancements in machine teaching, specifically the data progr…
Multi-Frame Cross-Entropy Training for Convolutional Neural Networks in Speech Recognition
Tom Sercu, Neil Mallinar
We introduce Multi-Frame Cross-Entropy training (MFCE) for convolutional neural network acoustic models. Recognizing that similar to RNNs, CNNs are in nature sequence models that t…
Bootstrapping Conversational Agents With Weak Supervision
Neil Mallinar, Abhishek Shah, Rajendra Ugrani +9
Many conversational agents in the market today follow a standard bot development framework which requires training intent classifiers to recognize user input. The need to create a…
Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition
Chun-Fu Chen, Quanfu Fan, Neil Mallinar +2
In this paper, we propose a novel Convolutional Neural Network (CNN) architecture for learning multi-scale feature representations with good tradeoffs between speed and accuracy. T…
Deep Canonically Correlated LSTMs
Neil Mallinar, Corbin Rosset
We examine Deep Canonically Correlated LSTMs as a way to learn nonlinear transformations of variable length sequences and embed them into a correlated, fixed dimensional space. We…
Probabilistic Cross-Identification of Galaxies with Realistic Clustering
Neil Mallinar, Tamas Budavari, Gerard Lemson
Probabilistic cross-identification has been successfully applied to a number of problems in astronomy from matching simple point sources to associating stars with unknown proper mo…