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07/25/2023
Implicitly Normalized Explicitly Regularized Density Estimation
We propose a new approach to non-parametric density estimation, that is ...
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03/12/2022
Whats Missing? Learning Hidden Markov Models When the Locations of Missing Observations are Unknown
The Hidden Markov Model (HMM) is one of the most widely used statistical...
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02/07/2021
Dimension Free Generalization Bounds for Non Linear Metric Learning
In this work we study generalization guarantees for the metric learning ...
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06/13/2019
Topic Modeling via Full Dependence Mixtures
We consider the topic modeling problem for large datasets. For this prob...
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06/13/2019
Variance Estimation For Online Regression via Spectrum Thresholding
We consider the online linear regression problem, where the predictor ve...
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12/17/2018
Multi Instance Learning For Unbalanced Data
In the context of Multi Instance Learning, we analyze the Single Instanc...
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09/16/2018
On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters
Kalman filter is a key tool for time-series forecasting and analysis. We...
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04/11/2018
Interdependent Gibbs Samplers
Gibbs sampling, as a model learning method, is known to produce the most...
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05/09/2016
Clustering Time Series and the Surprising Robustness of HMMs
Suppose that we are given a time series where consecutive samples are be...
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04/26/2015
