75 citations · 167 across the 8 of their papers we have counts for
9 papers
Toward Pareto Efficient Fairness-Utility Trade-off inRecommendation through Reinforcement Learning
Yingqiang Ge, Xiaoting Zhao, Lucia Yu +4
The issue of fairness in recommendation is becoming increasingly essential as Recommender Systems touch and influence more and more people in their daily lives. In fairness-aware r…
Wannier functions using a discrete variable representation for optical lattices
Saurabh Paul, Eite Tiesinga
We propose a numerical method using the discrete variable representation (DVR) for constructing real-valued Wannier functions localized in a unit cell for both symmetric and asymme…
A Hubbard model for ultracold bosonic atoms interacting via zero-point-energy induced three-body interactions
Saurabh Paul, P. R. Johnson, Eite Tiesinga
We show that for ultra-cold neutral bosonic atoms held in a three-dimensional periodic potential or optical lattice, a Hubbard model with dominant, attractive three-body interactio…
Column Selection via Adaptive Sampling
Saurabh Paul, Malik Magdon-Ismail, Petros Drineas
Selecting a good column (or row) subset of massive data matrices has found many applications in data analysis and machine learning. We propose a new adaptive sampling algorithm tha…
Large effective three-body interaction in a double-well optical lattice
Saurabh Paul, Eite Tiesinga
We study ultracold atoms in an optical lattice with two local minima per unit cell and show that the low energy states of a multi-band Bose-Hubbard (BH) Hamiltonian with only pair-…
Feature Selection for Ridge Regression with Provable Guarantees
Saurabh Paul, Petros Drineas
We introduce single-set spectral sparsification as a deterministic sampling based feature selection technique for regularized least squares classification, which is the classificat…
Feature Selection for Linear SVM with Provable Guarantees
Saurabh Paul, Malik Magdon-Ismail, Petros Drineas
We give two provably accurate feature-selection techniques for the linear SVM. The algorithms run in deterministic and randomized time respectively. Our algorithms can be used in a…
Formation and decay of Bose-Einstein condensates in an excited band of a double-well optical lattice
Saurabh Paul, Eite Tiesinga
We study the formation and collision-aided decay of an ultra-cold atomic Bose-Einstein condensate in the first excited band of a double-well 2D-optical lattice with weak harmonic c…
Random Projections for Linear Support Vector Machines
Saurabh Paul, Christos Boutsidis, Malik Magdon-Ismail +1
Let X be a data matrix of rank ρ, whose rows represent n points in d-dimensional space. The linear support vector machine constructs a hyperplane separator that maximizes the 1-nor…