
On Certifying Nonuniform Bound against Adversarial Attacks
This work studies the robustness certification problem of neural network...
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Depth and nonlinearity induce implicit exploration for RL
The question of how to explore, i.e., take actions with uncertain outcom...
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AMPNet: Asynchronous ModelParallel Training for Dynamic Neural Networks
New types of machine learning hardware in development and entering the m...
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MultiLevel Variational Autoencoder: Learning Disentangled Representations from Grouped Observations
We would like to learn a representation of the data which decomposes an ...
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Batch Policy Gradient Methods for Improving Neural Conversation Models
We study reinforcement learning of chatbots with recurrent neural networ...
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fGAN: Training Generative Neural Samplers using Variational Divergence Minimization
Generative neural samplers are probabilistic models that implement sampl...
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Theoretical and Experimental Analyses of TensorBased Regression and Classification
We theoretically and experimentally investigate tensorbased regression ...
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Interpolating Convex and NonConvex Tensor Decompositions via the Subspace Norm
We consider the problem of recovering a lowrank tensor from its noisy o...
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NormBased Capacity Control in Neural Networks
We investigate the capacity, convexity and characterization of a general...
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Spectral norm of random tensors
We show that the spectral norm of a random n_1× n_2×...× n_K tensor (or ...
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Convex Tensor Decomposition via Structured Schatten Norm Regularization
We discuss structured Schatten norms for tensor decomposition that inclu...
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The Algebraic Combinatorial Approach for LowRank Matrix Completion
We present a novel algebraic combinatorial view on lowrank matrix compl...
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Jointly Learning Multiple Measures of Similarities from Triplet Comparisons
Similarity between objects is multifaceted and it can be easier for hum...
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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...
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A Combinatorial Algebraic Approach for the Identifiability of LowRank Matrix Completion
In this paper, we review the problem of matrix completion and expose its...
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Discovering Emerging Topics in Social Streams via Link Anomaly Detection
Detection of emerging topics are now receiving renewed interest motivate...
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Sharp Convergence Rate and Support Consistency of Multiple Kernel Learning with Sparse and Dense Regularization
We theoretically investigate the convergence rate and support consistenc...
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Fast Convergence Rate of Multiple Kernel Learning with Elasticnet Regularization
We investigate the learning rate of multiple kernel leaning (MKL) with e...
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Regularization Strategies and Empirical Bayesian Learning for MKL
Multiple kernel learning (MKL), structured sparsity, and multitask lear...
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Estimation of lowrank tensors via convex optimization
In this paper, we propose three approaches for the estimation of the Tuc...
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Sparsityaccuracy tradeoff in MKL
We empirically investigate the best tradeoff between sparse and uniform...
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Modeling sparse connectivity between underlying brain sources for EEG/MEG
We propose a novel technique to assess functional brain connectivity in ...
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SuperLinear Convergence of Dual AugmentedLagrangian Algorithm for Sparsity Regularized Estimation
We analyze the convergence behaviour of a recently proposed algorithm fo...
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SpicyMKL
We propose a new optimization algorithm for Multiple Kernel Learning (MK...
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Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering
We propose the Gaussian attention model for contentbased neural memory ...
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Hierarchical Representations with Poincaré Variational AutoEncoders
The Variational AutoEncoder (VAE) model has become widely popular as a ...
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