activity
20142024
most citedA Novel Feature Selection and Extraction Technique for Classification

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.OS2024

File System Aging

Alex Conway, Ainesh Bakshi, Arghya Bhattacharya +11

File systems must allocate space for files without knowing what will be added or removed in the future. Over the life of a file system, this may cause suboptimal file placement dec…

cs.LG2023

Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems

Ainesh Bakshi, Allen Liu, Ankur Moitra +1

Recently Chen and Poor initiated the study of learning mixtures of linear dynamical systems. While linear dynamical systems already have wide-ranging applications in modeling time-…

cs.DS2023

Krylov Methods are (nearly) Optimal for Low-Rank Approximation

Ainesh Bakshi, Shyam Narayanan

We consider the problem of rank- low-rank approximation (LRA) in the matrix-vector product model under various Schatten norms: $$ \min_{\|u\|_2=1} \|A (I - u u^\top)\|_{\mathcal…

math.OC2023

A New Approach to Learning Linear Dynamical Systems

Ainesh Bakshi, Allen Liu, Ankur Moitra +1

Linear dynamical systems are the foundational statistical model upon which control theory is built. Both the celebrated Kalman filter and the linear quadratic regulator require kno…

cs.DS20161 cited

Polynomial Time Algorithm for -Stable Clustering Instances

Ainesh Bakshi, Nadiia Chepurko

Clustering with most objective functions is NP-Hard, even to approximate well in the worst case. Recently, there has been work on exploring different notions of stability which len…

cs.LG20142 cited

A Novel Feature Selection and Extraction Technique for Classification

Kratarth Goel, Raunaq Vohra, Ainesh Bakshi

This paper presents a versatile technique for the purpose of feature selection and extraction - Class Dependent Features (CDFs). We use CDFs to improve the accuracy of classificati…