1,736,842 research outputs found
“The media will always have axes to grind but the police have the capacity to project their side of the story better” – Neeraj Kumar
No full textNeeraj Kumar recently retired as the Commissioner of Police Delhi, having served in the Indian Police Service for over 37 years in a wide range of roles. He has now penned his first book, a collection of stories pertaining to high-profile cases solved during his nine year tenure at the Central Bureau of Investigation. Ahead of the London launch of the book, he spoke to Sonali Campion about the IPS, security and corruption in India. Dial D for Don: Inside stories of CBI missions will be launched at the Nehru Centre on 13 July at 6.30pm. The event is free and open to all and will include a panel with leading journalist Owen Bennett Jones and the author. Details here
Recommended from our members
Conversation about local customs and traditions
No full textNeeraj and Rajdeep discuss their customs and traditions, debating whether some of them should be preserved or discarded. The recording was made at Umar Homestay in Rakchham village
Learning Generalized Depth Three Arithmetic Circuits in the Non-Degenerate Case
Full text linkConsider a homogeneous degree d polynomial f = T₁ + ⋯ + T_s, T_i = g_i(_{i,1}, …, _{i, m}) where g_i’s are homogeneous m-variate degree d polynomials and _{i,j}’s are linear polynomials in n variables. We design a (randomized) learning algorithm that given black-box access to f, computes black-boxes for the T_i’s. The running time of the algorithm is poly(n, m, d, s) and the algorithm works under some non-degeneracy conditions on the linear forms and the g_i’s, and some additional technical assumptions n ≥ (md)², s ≤ n^{d/4}. The non-degeneracy conditions on _{i,j}’s constitute non-membership in a variety, and hence are satisfied when the coefficients of _{i,j}’s are chosen uniformly and randomly from a large enough set. The conditions on g_i’s are satisfied for random polynomials and also for natural polynomials common in the study of arithmetic complexity like determinant, permanent, elementary symmetric polynomial, iterated matrix multiplication. A particularly appealing algorithmic corollary is the following: Given black-box access to an f = Det_r(L^(1)) + … + Det_r(L^(s)), where L^(k) = (_{i,j}^(k))_{i,j} with _{i,j}^(k)’s being linear forms in n variables chosen randomly, there is an algorithm which in time poly(n, r) outputs matrices (M^(k))_k of linear forms s.t. there exists a permutation π: [s] → [s] with Det_r(M^(k)) = Det_r(L^(π(k))).
Our work follows the works [Neeraj Kayal and Chandan Saha, 2019; Garg et al., 2020] which use lower bound methods in arithmetic complexity to design average case learning algorithms. It also vastly generalizes the result in [Neeraj Kayal and Chandan Saha, 2019] about learning depth three circuits, which is a special case where each g_i is just a monomial. At the core of our algorithm is the partial derivative method which can be used to prove lower bounds for generalized depth three circuits. To apply the general framework in [Neeraj Kayal and Chandan Saha, 2019; Garg et al., 2020], we need to establish that the non-degeneracy conditions arising out of applying the framework with the partial derivative method are satisfied in the random case. We develop simple but general and powerful tools to establish this, which might be useful in designing average case learning algorithms for other arithmetic circuit models
Neeraj Upadhyay's Quick Files
No full textThe Quick Files feature was discontinued and it’s files were migrated into this Project on March 11, 2022. The file URL’s will still resolve properly, and the Quick Files logs are available in the Project’s Recent Activity
Analyzing compute-intensive software performance
Full text linkThesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 41).by Neeraj Gupta.M.S
Neeraj Upadhyay's Quick Files
No full textThe Quick Files feature was discontinued and it’s files were migrated into this Project on March 11, 2022. The file URL’s will still resolve properly, and the Quick Files logs are available in the Project’s Recent Activity
- …
