activity
20192025
most citedScalable Realistic Recommendation Datasets through Fractal Expansions

16 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

math.NT2025

On the Minimality of the Conductor for Elliptic Curve -Functions

K. Lakshmanan

We investigate the role of the conductor in analytic rank bounds for elliptic curves over \(\mathbb{Q}\). Let \(E/\mathbb{Q}\) be an elliptic curve with conductor \(N_E\). We consi…

cs.CC2025

Computational Complexity of Finding Subgroups of a Given Order

K. Lakshmanan

We study the problem of finding a subgroup of a given order in a finite group, where the group is represented by its Cayley table. We analyze the complexity of the problem in the s…

math.NT2024

Primes and Bivariate Polynomials without Constant Terms: A Recursive Algorithm

K. Lakshmanan

We investigate the computational problem of determining whether a bivariate polynomial with non-negative coefficients and no constant term can attain a prime value. While classical…

math.OC2024

Uncomputability of Global Optima for Nonconvex Functions in the Oracle Model

K Lakshmanan

While it is well known that finding approximate optima of non-convex functions is computationally intractable, we show that the problem is, in fact, uncomputable in the oracle mode…

cs.LG2019★ 2 cited

Scaling Up Collaborative Filtering Data Sets through Randomized Fractal Expansions

Francois Belletti, Karthik Lakshmanan, Walid Krichene +7

Recommender system research suffers from a disconnect between the size of academic data sets and the scale of industrial production systems. In order to bridge that gap, we propose…

cs.IR2019★ 16 cited

Scalable Realistic Recommendation Datasets through Fractal Expansions

Francois Belletti, Karthik Lakshmanan, Walid Krichene +2

Recommender System research suffers currently from a disconnect between the size of academic data sets and the scale of industrial production systems. In order to bridge that gap w…