
On Certifying Nonuniform Bound against Adversarial Attacks
This work studies the robustness certification problem of neural network...
03/15/2019 ∙ by Chen Liu, et al. ∙ 8 ∙ shareread it

Depth and nonlinearity induce implicit exploration for RL
The question of how to explore, i.e., take actions with uncertain outcom...
05/29/2018 ∙ by Justas Dauparas, et al. ∙ 4 ∙ shareread it

AMPNet: Asynchronous ModelParallel Training for Dynamic Neural Networks
New types of machine learning hardware in development and entering the m...
05/27/2017 ∙ by Alexander L. Gaunt, et al. ∙ 0 ∙ shareread it

MultiLevel Variational Autoencoder: Learning Disentangled Representations from Grouped Observations
We would like to learn a representation of the data which decomposes an ...
05/24/2017 ∙ by Diane Bouchacourt, et al. ∙ 0 ∙ shareread it

Batch Policy Gradient Methods for Improving Neural Conversation Models
We study reinforcement learning of chatbots with recurrent neural networ...
02/10/2017 ∙ by Kirthevasan Kandasamy, et al. ∙ 0 ∙ shareread it

fGAN: Training Generative Neural Samplers using Variational Divergence Minimization
Generative neural samplers are probabilistic models that implement sampl...
06/02/2016 ∙ by Sebastian Nowozin, et al. ∙ 0 ∙ shareread it

Theoretical and Experimental Analyses of TensorBased Regression and Classification
We theoretically and experimentally investigate tensorbased regression ...
09/06/2015 ∙ by Kishan Wimalawarne, et al. ∙ 0 ∙ shareread it

Interpolating Convex and NonConvex Tensor Decompositions via the Subspace Norm
We consider the problem of recovering a lowrank tensor from its noisy o...
03/18/2015 ∙ by Qinqing Zheng, et al. ∙ 0 ∙ shareread it

NormBased Capacity Control in Neural Networks
We investigate the capacity, convexity and characterization of a general...
02/27/2015 ∙ by Behnam Neyshabur, et al. ∙ 0 ∙ shareread it

Spectral norm of random tensors
We show that the spectral norm of a random n_1× n_2×...× n_K tensor (or ...
07/07/2014 ∙ by Ryota Tomioka, et al. ∙ 0 ∙ shareread it

Convex Tensor Decomposition via Structured Schatten Norm Regularization
We discuss structured Schatten norms for tensor decomposition that inclu...
03/26/2013 ∙ by Ryota Tomioka, et al. ∙ 0 ∙ shareread it

The Algebraic Combinatorial Approach for LowRank Matrix Completion
We present a novel algebraic combinatorial view on lowrank matrix compl...
11/17/2012 ∙ by Franz J Király, et al. ∙ 0 ∙ shareread it

Jointly Learning Multiple Measures of Similarities from Triplet Comparisons
Similarity between objects is multifaceted and it can be easier for hum...
03/05/2015 ∙ by Liwen Zhang, et al. ∙ 0 ∙ shareread it

In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
We present experiments demonstrating that some other form of capacity co...
12/20/2014 ∙ by Behnam Neyshabur, et al. ∙ 0 ∙ shareread it

A Combinatorial Algebraic Approach for the Identifiability of LowRank Matrix Completion
In this paper, we review the problem of matrix completion and expose its...
06/27/2012 ∙ by Franz Király, et al. ∙ 0 ∙ shareread it

Discovering Emerging Topics in Social Streams via Link Anomaly Detection
Detection of emerging topics are now receiving renewed interest motivate...
10/13/2011 ∙ by Toshimitsu Takahashi, et al. ∙ 0 ∙ shareread it

Sharp Convergence Rate and Support Consistency of Multiple Kernel Learning with Sparse and Dense Regularization
We theoretically investigate the convergence rate and support consistenc...
03/27/2011 ∙ by Taiji Suzuki, et al. ∙ 0 ∙ shareread it

Fast Convergence Rate of Multiple Kernel Learning with Elasticnet Regularization
We investigate the learning rate of multiple kernel leaning (MKL) with e...
03/02/2011 ∙ by Taiji Suzuki, et al. ∙ 0 ∙ shareread it

Regularization Strategies and Empirical Bayesian Learning for MKL
Multiple kernel learning (MKL), structured sparsity, and multitask lear...
11/13/2010 ∙ by Ryota Tomioka, et al. ∙ 0 ∙ shareread it

Estimation of lowrank tensors via convex optimization
In this paper, we propose three approaches for the estimation of the Tuc...
10/05/2010 ∙ by Ryota Tomioka, et al. ∙ 0 ∙ shareread it

Sparsityaccuracy tradeoff in MKL
We empirically investigate the best tradeoff between sparse and uniform...
01/15/2010 ∙ by Ryota Tomioka, et al. ∙ 0 ∙ shareread it

Modeling sparse connectivity between underlying brain sources for EEG/MEG
We propose a novel technique to assess functional brain connectivity in ...
12/12/2009 ∙ by Stefan Haufe, et al. ∙ 0 ∙ shareread it

SuperLinear Convergence of Dual AugmentedLagrangian Algorithm for Sparsity Regularized Estimation
We analyze the convergence behaviour of a recently proposed algorithm fo...
11/20/2009 ∙ by Ryota Tomioka, et al. ∙ 0 ∙ shareread it

SpicyMKL
We propose a new optimization algorithm for Multiple Kernel Learning (MK...
09/28/2009 ∙ by Taiji Suzuki, et al. ∙ 0 ∙ shareread it

Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering
We propose the Gaussian attention model for contentbased neural memory ...
11/07/2016 ∙ by Liwen Zhang, et al. ∙ 0 ∙ shareread it

Hierarchical Representations with Poincaré Variational AutoEncoders
The Variational AutoEncoder (VAE) model has become widely popular as a ...
01/17/2019 ∙ by Emile Mathieu, et al. ∙ 0 ∙ shareread it