16 citations · 52 across the 7 of their papers we have counts for
9 papers
Compact Tensor Pooling for Visual Question Answering
Yang Shi, Tommaso Furlanello, Anima Anandkumar
Performing high level cognitive tasks requires the integration of feature maps with drastically different structure. In Visual Question Answering (VQA) image descriptors have spati…
Tensor Contraction Layers for Parsimonious Deep Nets
Jean Kossaifi, Aran Khanna, Zachary C. Lipton +2
Tensors offer a natural representation for many kinds of data frequently encountered in machine learning. Images, for example, are naturally represented as third order tensors, whe…
Experimental results : Reinforcement Learning of POMDPs using Spectral Methods
Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
We propose a new reinforcement learning algorithm for partially observable Markov decision processes (POMDP) based on spectral decomposition methods. While spectral methods have be…
Efficient approaches for escaping higher order saddle points in non-convex optimization
Anima Anandkumar, Rong Ge
Local search heuristics for non-convex optimizations are popular in applied machine learning. However, in general it is hard to guarantee that such algorithms even converge to a lo…
Convolutional Dictionary Learning through Tensor Factorization
Furong Huang, Animashree Anandkumar
Tensor methods have emerged as a powerful paradigm for consistent learning of many latent variable models such as topic models, independent component analysis and dictionary learni…
A Scale Mixture Perspective of Multiplicative Noise in Neural Networks
Eric Nalisnick, Anima Anandkumar, Padhraic Smyth
Corrupting the input and hidden layers of deep neural networks (DNNs) with multiplicative noise, often drawn from the Bernoulli distribution (or 'dropout'), provides regularization…