
Amazon SageMaker Automatic Model Tuning: Scalable Blackbox Optimization
Tuning complex machine learning systems is challenging. Machine learning...
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Amazon SageMaker Autopilot: a white box AutoML solution at scale
AutoML systems provide a blackbox solution to machine learning problems...
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NonStationary Latent Bandits
Users of recommender systems often behave in a nonstationary fashion, d...
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Scalable BottomUp Hierarchical Clustering
Bottomup algorithms such as the classic hierarchical agglomerative clus...
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Unsupervised Abstractive Dialogue Summarization for TeteaTetes
Highquality dialoguesummary paired data is expensive to produce and do...
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Big Bird: Transformers for Longer Sequences
Transformersbased models, such as BERT, have been one of the most succe...
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Latent Bandits Revisited
A latent bandit problem is one in which the learning agent knows the arm...
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PiecewiseStationary OffPolicy Optimization
Offpolicy learning is a framework for evaluating and optimizing policie...
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Anchor Transform: Learning Sparse Representations of Discrete Objects
Learning continuous representations of discrete objects such as text, us...
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State Space LSTM Models with Particle MCMC Inference
Long ShortTerm Memory (LSTM) is one of the most powerful sequence model...
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Explaining reviews and ratings with PACO: Poisson Additive CoClustering
Understanding a user's motivations provides valuable information beyond ...
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High Performance Latent Variable Models
Latent variable models have accumulated a considerable amount of interes...
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ACCAMS: Additive CoClustering to Approximate Matrices Succinctly
Matrix completion and approximation are popular tools to capture a user'...
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Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream
Topic models have proven to be a useful tool for discovering latent stru...
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MedLDA: A General Framework of Maximum Margin Supervised Topic Models
Supervised topic models utilize document's side information for discover...
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Amr Ahmed
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