89 citations · 118 across the 9 of their papers we have counts for
9 papers
On a Bernoulli Autoregression Framework for Link Discovery and Prediction
Xiaohan Yan, Avleen S. Bijral
We present a dynamic prediction framework for binary sequences that is based on a Bernoulli generalization of the auto-regressive process. Our approach lends itself easily to varia…
Survey Data and Human Computation for Improved Flu Tracking
Stefan Wojcik, Avleen Bijral, Richard Johnston +5
While digital trace data from sources like search engines hold enormous potential for tracking and understanding human behavior, these streams of data lack information about the ac…
On Selecting Stable Predictors in Time Series Models
Avleen S. Bijral
We extend the feature selection methodology to dependent data and propose a novel time series predictor selection scheme that accommodates statistical dependence in a more typical…
NonSTOP: A NonSTationary Online Prediction Method for Time Series
Christopher Xie, Avleen Bijral, Juan Lavista Ferres
We present online prediction methods for time series that let us explicitly handle nonstationary artifacts (e.g. trend and seasonality) present in most real time series. Specifical…
Data Dependent Convergence for Distributed Stochastic Optimization
Avleen S. Bijral
In this dissertation we propose alternative analysis of distributed stochastic gradient descent (SGD) algorithms that rely on spectral properties of the data covariance. As a conse…
Predicting Unemployment Claims Using Regional and Exogenous Signals: A Sparse Modeling Approach
Avleen S. Bijral, Richard Johnston, Juan Lavista Ferres
In this paper we apply a time series based Vector Auto Regressive (VAR) approach to the problem of predicting unemployment insurance claims in different census regions of the Unite…