4 papers · 1 filter
Stochastic Trust Region Inexact Newton Method for Large-scale Machine Learning
Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya
Nowadays stochastic approximation methods are one of the major research direction to deal with the large-scale machine learning problems. From stochastic first order methods, now t…
Online learning using multiple times weight updating
Charanjeet, Anuj Sharma
Online learning makes sequence of decisions with partial data arrival where next movement of data is unknown. In this paper, we have presented a new technique as multiple times wei…
SAAGs: Biased Stochastic Variance Reduction Methods for Large-scale Learning
Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya
Stochastic approximation is one of the effective approach to deal with the large-scale machine learning problems and the recent research has focused on reduction of variance, cause…
Temporal processing and context dependency in C. elegans mechanosensation
Mochi Liu, Anuj K Sharma, Joshua W Shaevitz +1
A quantitative understanding of how sensory signals are transformed into motor outputs places useful constraints on brain function and helps reveal the brain's underlying computati…