1,733,444 research outputs found
Chandan-IITI/One-Class-Kernel-ELM: First release of Kernel ELM (Kernel Ridge Regression) based One-class Classifiers
<p>Toolbox for Kernel Extreme Learning Machine (KELM) or Kernel Ridge Regression (KRR) based One-class classifiers. This toolbox is completely compatible with the features of the most popular toolbox for the One-class Classification task i.e. DD Toolbox. If you are using this toolbox then please cite the following paper and this repository:</p>
<p>Chandan Gautam, Aruna Tiwari, Qian Leng, On the construction of extreme learning machine for online and offline one-class classification—An expanded toolbox, Neurocomputing, Volume 261, 2017, Pages 126-143, ISSN 0925-2312, <a href="http://dx.doi.org/10.1016/j.neucom.2016.04.070">http://dx.doi.org/10.1016/j.neucom.2016.04.070</a>. (<a href="http://www.sciencedirect.com/science/article/pii/S0925231217302096">http://www.sciencedirect.com/science/article/pii/S0925231217302096</a>)</p>
Pliocene surface temperature data for Multi-variate factorisation methods
This dataset contains reference height temperatures from the simulations of Chandan and Peltier (2017, 2018), Clim Past, that can be used to study various multivariate factorization methods. The files are named by the simulation names used in these papers
A life in the world : U. R. Ananthamurthy in conversation with Chandan Gowda
A fascinating portrait of the life and ideas of the great Indian writer and public intellectual, U.R. Ananthamurthy. Between 2012 and 2013, Ananthamurthy shared his personal experiences in a series of lively conversations with academic and writer Chandan Gowda, and reflected on issues that would preoccupy him until the end. Besides the vivid accounts of his childhood, friendships, the evolution of his intellectual life, and public involvements, his passionate ideas on tradition, on India’s political culture, and on language and writing make the conversations an engaging and valuable document. A Life in the World – perhaps the first exercise of its kind done with an Indian writer – will enthral both general readers as well as admirers of Ananthamurthy’s works
Shigar's Prosperity and the Legendary Chandan Tree
Once upon a time, a saying was famous throughout Baltistan: "If you lack food or prosperity, go to Shigar". This was because Shigar was known for its abundant agriculture and fertile land, unlike Khaplu and Kharmang, where the scarcity of land limited agricultural activities. The secret to Shigar's prosperity [reportedly] laid in a Chandan tree, known locally as "Chandanne nkholam".This ancient tree stood tall at a spot from where the entire lush and thriving Shigar valley was visible. Invaders once attacked and destroyed much of Shigar, including its greenery. However, they were baffled when, upon returning to the viewpoint (initially called "Nar e lo"), they saw Shigar green and flourishing again. They could not comprehend how the valley remained verdant after their destruction. To uncover the mystery, the invaders offered money to an old woman, who revealed the secret: the Chandan tree was the source of Shigar's vitality. They cut down the tree, but the valley's greenery persisted. Returning to the old woman, they were told to burn the tree's roots using apricot seed kernels. Even then, the greenery diminished only slightly because a part of the root remained, sustaining Shigar's verdancy to this day. Years later, an argument broke out between a man from Skardu and one from Shigar. The Skardu man insulted the Shigar man by calling him a "Cow thief." The Shigar man, known for his poetic nature, responded in verse, highlighting Shigar's wealth and abundance, contrasting it with Skardu, where families shared a single goat for milk. He spoke of Shigar as a land of gold, milk, diamonds, and the Chandan tree. He implied that while Skardu struggled for basic sustenance, Shigar thrived with livestock and agriculture. His poetic retort, mentioning the Chandan tree, underscored Shigar's enduring prosperity. The Shigar man apologized if his words offended, explaining that the tale was shared to emphasize Shigar's richness and the legendary tree's role in their heritage.2.7.4.
Learning Generalized Depth Three Arithmetic Circuits in the Non-Degenerate Case
Consider 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
The Possibilities of Punjabi : Modern Punjabi Literature in India, Pakistan, and Beyond : [Interview with Amarjit Chandan]
In this 2015 interview for Dr. Anne Murphy’s SSHRC-funded project “Transnational modern Punjabi literature and the pursuit of the secular,” Amarjit Chandan, born in Nairobi, Kenya in 1946, a prominent Punjabi poet and promoter of Punjabi language, discusses how the relationship between literature and politics should not be overemphasized and that each should be given their own space. In this light, Amarjit Chandan considers himself a pure poet, although he does acknowledge that politics are unavoidable. Above all, Amarjit Chandan posits that poetry is a medium to express emotion, the soul and the heart. Poetry, for Amarjit Chandan, allows one to access feelings we often avoid such as sadness. Interview by Dr. Anne Murphy. Funded by SSHRC Insight Development (430-2013-000121) and Insight (435-2017-0406) Grants.Arts, Faculty ofAsian Studies, Department ofUnreviewedFacult
Transition Metal-Radical Complexes and Their Catalytic Reactivity
by Chandan MukherjeePaderborn, Univ., Diss., 200
‘A Present Moment, More Present: John Berger’s Politics of Intensity’
Published also under the short title 'Stars' this essay was written for Gunaratnam, Y. and A. Chandan (editors) A Jar of Wild Flowers: Essays in Honour of John Berger (2016) London: Zed. It concerns the concept of intensity in Berger's writing, not as a simple theatricality, nor a search for something truer to life, but is a philosophical stance that concerns political equality. It discusses this in relation to a moment in my own research in the cemetery in Santiago, Chile
Data for Chandan in Fig2 from The mechanism of delayed release in earthquake-induced avalanches
A kmz file in compressed format, extracted from Google Earth and used to calculate the statistics of slope angles for Chandan
Data for Chandan in Fig2 from The mechanism of delayed release in earthquake-induced avalanches
A kmz file in compressed format, extracted from Google Earth and used to calculate the statistics of slope angles for Chandan
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