
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations
Deep learning based recommender systems (DLRSs) often have embedding lay...
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Learning to Structure Longterm Dependence for Sequential Recommendation
Sequential recommendation recommends items based on sequences of users' ...
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MultiDomain Neural Machine Translation with WordLevel Adaptive Layerwise Domain Mixing
Many multidomain neural machine translation (NMT) models achieve knowle...
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Feature Partitioning for Efficient MultiTask Architectures
Multitask learning holds the promise of less data, parameters, and time...
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Neural Logic Machines
We propose the Neural Logic Machine (NLM), a neuralsymbolic architectur...
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Prioraware Neural Network for PartiallySupervised MultiOrgan Segmentation
Accurate multiorgan abdominal CT segmentation is essential to many clin...
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Doubly Sparse: Sparse Mixture of Sparse Experts for Efficient Softmax Inference
Computations for the softmax function are significantly expensive when t...
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Neural PhrasetoPhrase Machine Translation
In this paper, we propose Neural PhrasetoPhrase Machine Translation (N...
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Fully Supervised Speaker Diarization
In this paper, we propose a fully supervised speaker diarization approac...
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Rate Distortion For Model Compression: From Theory To Practice
As the size of neural network models increases dramatically today, study...
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Subgoal Discovery for Hierarchical Dialogue Policy Learning
Developing conversational agents to engage in complex dialogues is chall...
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Attentionbased Graph Neural Network for Semisupervised Learning
Recently popularized graph neural networks achieve the stateoftheart ...
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Thoracic Disease Identification and Localization with Limited Supervision
Accurate identification and localization of abnormalities from radiology...
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How to Train Triplet Networks with 100K Identities?
Training triplet networks with largescale data is challenging in face r...
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Model Distillation with Knowledge Transfer from Face Classification to Alignment and Verification
Knowledge distillation is a potential solution for model compression. Th...
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Towards Neural Phrasebased Machine Translation
In this paper, we present Neural Phrasebased Machine Translation (NPMT)...
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Scaffolding Networks: Incremental Learning and Teaching Through Questioning
We introduce a new paradigm of learning for reasoning, understanding, an...
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Sequence Modeling via Segmentations
Segmental structure is a common pattern in many types of sequences such ...
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TopicRNN: A Recurrent Neural Network with LongRange Semantic Dependency
In this paper, we propose TopicRNN, a recurrent neural network (RNN)bas...
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Scalable Modeling of Conversationalrole based Selfpresentation Characteristics in Large Online Forums
Online discussion forums are complex webs of overlapping subcommunities ...
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Deep Speech 2: EndtoEnd Speech Recognition in English and Mandarin
We show that an endtoend deep learning approach can be used to recogni...
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A General Method for Robust Bayesian Modeling
Robust Bayesian models are appealing alternatives to standard models, pr...
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Embarrassingly Parallel Variational Inference in Nonconjugate Models
We develop a parallel variational inference (VI) procedure for use in da...
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Asymptotically Exact, Embarrassingly Parallel MCMC
Communication costs, resulting from synchronization requirements during ...
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A Nested HDP for Hierarchical Topic Models
We develop a nested hierarchical Dirichlet process (nHDP) for hierarchic...
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Nested Hierarchical Dirichlet Processes
We develop a nested hierarchical Dirichlet process (nHDP) for hierarchic...
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Variational Inference in Nonconjugate Models
Meanfield variational methods are widely used for approximate posterior...
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Stochastic Variational Inference
We develop stochastic variational inference, a scalable algorithm for ap...
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Latent Collaborative Retrieval
Retrieval tasks typically require a ranking of items given a query. Coll...
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Continuous Time Dynamic Topic Models
In this paper, we develop the continuous time dynamic topic model (cDTM)...
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A SplitMerge MCMC Algorithm for the Hierarchical Dirichlet Process
The hierarchical Dirichlet process (HDP) has become an important Bayesia...
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The Discrete Infinite Logistic Normal Distribution
We present the discrete infinite logistic normal distribution (DILN), a ...
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