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7 papers · 2 filters
Lattice Rescoring Strategies for Long Short Term Memory Language Models in Speech Recognition
Shankar Kumar, Michael Nirschl, Daniel Holtmann-Rice +3
Recurrent neural network (RNN) language models (LMs) and Long Short Term Memory (LSTM) LMs, a variant of RNN LMs, have been shown to outperform traditional N-gram LMs on speech rec…
Intriguing Properties of Adversarial Examples
Ekin D. Cubuk, Barret Zoph, Samuel S. Schoenholz +1
It is becoming increasingly clear that many machine learning classifiers are vulnerable to adversarial examples. In attempting to explain the origin of adversarial examples, previo…
The (Un)reliability of saliency methods
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo +5
Saliency methods aim to explain the predictions of deep neural networks. These methods lack reliability when the explanation is sensitive to factors that do not contribute to the m…
Similarity-based Multi-label Learning
Ryan A. Rossi, Nesreen K. Ahmed, Hoda Eldardiry +1
Multi-label classification is an important learning problem with many applications. In this work, we propose a principled similarity-based approach for multi-label learning called…
On the challenges of learning with inference networks on sparse, high-dimensional data
Rahul G. Krishnan, Dawen Liang, Matthew Hoffman
We study parameter estimation in Nonlinear Factor Analysis (NFA) where the generative model is parameterized by a deep neural network. Recent work has focused on learning such mode…
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Maithra Raghu, Justin Gilmer, Jason Yosinski +1
We propose a new technique, Singular Vector Canonical Correlation Analysis (SVCCA), a tool for quickly comparing two representations in a way that is both invariant to affine trans…