Results for "Balaraman Ravindran"

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SLAM-Safe Planner: Preventing Monocular SLAM Failure using Reinforcement LearningJul 26 2016Sep 16 2016Effective SLAM using a single monocular camera is highly preferred due to its simplicity. However, when compared to trajectory planning methods using depth-based SLAM, Monocular SLAM in loop does need additional considerations. One main reason being that ... More
Hypergraph Clustering: A Modularity Maximization ApproachDec 28 2018Clustering on hypergraphs has been garnering increased attention with potential applications in network analysis, VLSI design and computer vision, among others. In this work, we generalize the framework of modularity maximization for clustering on hypergraphs. ... More
Rate of Change Analysis for Interestingness MeasuresDec 14 2017The use of Association Rule Mining techniques in diverse contexts and domains has resulted in the creation of numerous interestingness measures. This, in turn, has motivated researchers to come up with various classification schemes for these measures. ... More
Polyphonic Music Composition with LSTM Neural Networks and Reinforcement LearningFeb 05 2019In the domain of algorithmic music composition, machine learning-driven systems eliminate the need for carefully hand-crafting rules for composition. In particular, the capability of recurrent neural networks to learn complex temporal patterns lends itself ... More
Optimal Resampling for Learning Small ModelsMay 04 2019Models often need to be constrained to a certain size for them to be considered interpretable, for e.g., a decision tree of depth 5 is much easier to make sense of than one of depth 30. This suggests a trade-off between interpretability and accuracy. ... More
Polyphonic Music Composition with LSTM Neural Networks and Reinforcement LearningFeb 05 2019Mar 03 2019In the domain of algorithmic music composition, machine learning-driven systems eliminate the need for carefully hand-crafting rules for composition. In particular, the capability of recurrent neural networks to learn complex temporal patterns lends itself ... More
RAIL: Risk-Averse Imitation LearningJul 20 2017Nov 29 2017Imitation learning algorithms learn viable policies by imitating an expert's behavior when reward signals are not available. Generative Adversarial Imitation Learning (GAIL) is a state-of-the-art algorithm for learning policies when the expert's behavior ... More
Linear Bandit algorithms using the BootstrapMay 04 2016This study presents two new algorithms for solving linear stochastic bandit problems. The proposed methods use an approach from non-parametric statistics called bootstrapping to create confidence bounds. This is achieved without making any assumptions ... More
Learning Interpretable Models Using an OracleJun 17 2019As Machine Learning (ML) becomes pervasive in various real world systems, the need for models to be interpretable or explainable has increased. We focus on interpretability, noting that models often need to be constrained in size for them to be considered ... More
Scalable Positional Analysis for Studying Evolution of Nodes in NetworksFeb 16 2014Jan 20 2015In social network analysis, the fundamental idea behind the notion of position is to discover actors who have similar structural signatures. Positional analysis of social networks involves partitioning the actors into disjoint sets using a notion of equivalence ... More
Shared Learning : Enhancing Reinforcement in $Q$-EnsemblesSep 14 2017Deep Reinforcement Learning has been able to achieve amazing successes in a variety of domains from video games to continuous control by trying to maximize the cumulative reward. However, most of these successes rely on algorithms that require a large ... More
Fractional Moments on Bandit ProblemsFeb 14 2012Reinforcement learning addresses the dilemma between exploration to find profitable actions and exploitation to act according to the best observations already made. Bandit problems are one such class of problems in stateless environments that represent ... More
Successor Options: An Option Discovery Framework for Reinforcement LearningMay 14 2019The options framework in reinforcement learning models the notion of a skill or a temporally extended sequence of actions. The discovery of a reusable set of skills has typically entailed building options, that navigate to bottleneck states. This work ... More
HEMI: Hyperedge Majority Influence MaximizationJun 16 2016In this work, we consider the problem of influence maximization on a hypergraph. We first extend the Independent Cascade (IC) model to hypergraphs, and prove that the traditional influence maximization problem remains submodular. We then present a variant ... More
TSEB: More Efficient Thompson Sampling for Policy LearningOct 10 2015In model-based solution approaches to the problem of learning in an unknown environment, exploring to learn the model parameters takes a toll on the regret. The optimal performance with respect to regret or PAC bounds is achievable, if the algorithm exploits ... More
Edge Replacement Grammars: A Formal Language Approach for Generating GraphsFeb 11 2019Graphs are increasingly becoming ubiquitous as models for structured data. A generative model that closely mimics the structural properties of a given set of graphs has utility in a variety of domains. Much of the existing work require that a large number ... More
Generalized Random Surfer-Pair ModelsJul 02 2019Jul 04 2019SimRank is a widely studied link-based similarity measure that is known for its simple, yet powerful philosophy that two nodes are similar if they are referenced by similar nodes. While this philosophy has been the basis of several improvements, there ... More
Exploration for Multi-task Reinforcement Learning with Deep Generative ModelsNov 29 2016Exploration in multi-task reinforcement learning is critical in training agents to deduce the underlying MDP. Many of the existing exploration frameworks such as $E^3$, $R_{max}$, Thompson sampling assume a single stationary MDP and are not suitable for ... More
Discovering hierarchies using Imitation Learning from hierarchy aware policiesDec 01 2018Learning options that allow agents to exhibit temporally higher order behavior has proven to be useful in increasing exploration, reducing sample complexity and for various transfer scenarios. Deep Discovery of Options (DDO) is a generative algorithm ... More
Generalized Random Surfer-Pair ModelsJul 02 2019SimRank is a widely studied link-based similarity measure that is known for its simple, yet powerful philosophy that two nodes are similar if they are referenced by similar nodes. While this philosophy has been the basis of several improvements, there ... More
Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest PackingSep 05 2018Jan 26 2019Object detection in videos is an important task in computer vision for various applications such as object tracking, video summarization and video search. Although great progress has been made in improving the accuracy of object detection in recent years ... More
Dynamic Frame skip Deep Q NetworkMay 17 2016Jun 11 2016Deep Reinforcement Learning methods have achieved state of the art performance in learning control policies for the games in the Atari 2600 domain. One of the important parameters in the Arcade Learning Environment (ALE) is the frame skip rate. It decides ... More
An Active Learning Framework for Efficient Robust Policy SearchJan 01 2019Robust Policy Search is the problem of learning policies that do not degrade in performance when subject to unseen environment model parameters. It is particularly relevant for transferring policies learned in a simulation environment to the real world. ... More
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement LearningFeb 20 2017Reinforcement Learning algorithms can learn complex behavioral patterns for sequential decision making tasks wherein an agent interacts with an environment and acquires feedback in the form of rewards sampled from it. Traditionally, such algorithms make ... More
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement LearningMay 17 2019Shaping in humans and animals has been shown to be a powerful tool for learning complex tasks as compared to learning in a randomized fashion. This makes the problem less complex and enables one to solve the easier sub task at hand first. Generating a ... More
Diversity driven Attention Model for Query-based Abstractive SummarizationApr 26 2017Jul 13 2018Abstractive summarization aims to generate a shorter version of the document covering all the salient points in a compact and coherent fashion. On the other hand, query-based summarization highlights those points that are relevant in the context of a ... More
Thresholding Bandits with Augmented UCBApr 07 2017May 09 2017In this paper we propose the Augmented-UCB (AugUCB) algorithm for a fixed-budget version of the thresholding bandit problem (TBP), where the objective is to identify a set of arms whose quality is above a threshold. A key feature of AugUCB is that it ... More
Efficient-UCBV: An Almost Optimal Algorithm using Variance EstimatesNov 09 2017We propose a novel variant of the UCB algorithm (referred to as Efficient-UCB-Variance (EUCBV)) for minimizing cumulative regret in the stochastic multi-armed bandit (MAB) setting. EUCBV incorporates the arm elimination strategy proposed in UCB-Improved ... More
EPOpt: Learning Robust Neural Network Policies Using Model EnsemblesOct 05 2016Mar 03 2017Sample complexity and safety are major challenges when learning policies with reinforcement learning for real-world tasks, especially when the policies are represented using rich function approximators like deep neural networks. Model-based methods where ... More
A Reinforcement Learning Approach to Online Learning of Decision TreesJul 24 2015Online decision tree learning algorithms typically examine all features of a new data point to update model parameters. We propose a novel alternative, Reinforcement Learning- based Decision Trees (RLDT), that uses Reinforcement Learning (RL) to actively ... More
Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal ClusteringMay 17 2016Sep 20 2016This paper introduces an automated skill acquisition framework in reinforcement learning which involves identifying a hierarchical description of the given task in terms of abstract states and extended actions between abstract states. Identifying such ... More
Language Expansion In Text-Based GamesMay 17 2018Text-based games are suitable test-beds for designing agents that can learn by interaction with the environment in the form of natural language text. Very recently, deep reinforcement learning based agents have been successfully applied for playing text-based ... More
Learning to Mix n-Step Returns: Generalizing lambda-Returns for Deep Reinforcement LearningMay 21 2017Nov 05 2017Reinforcement Learning (RL) can model complex behavior policies for goal-directed sequential decision making tasks. A hallmark of RL algorithms is Temporal Difference (TD) learning: value function for the current state is moved towards a bootstrapped ... More
Learning to Multi-Task by Active SamplingFeb 20 2017May 21 2017One of the long-standing challenges in Artificial Intelligence for learning goal-directed behavior is to build a single agent which can solve multiple tasks. Recent progress in multi-task learning for goal-directed sequential problems has been in the ... More
Correlational Neural NetworksApr 27 2015Oct 12 2015Common Representation Learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, is receiving a lot of attention recently. Two popular paradigms here are Canonical Correlation Analysis (CCA) based approaches ... More
SLAM-Safe Planner: Preventing Monocular SLAM Failure using Reinforcement LearningJul 26 2016Mar 03 2017Effective SLAM using a single monocular camera is highly preferred due to its simplicity. However, when compared to trajectory planning methods using depth-based SLAM, Monocular SLAM in loop does need additional considerations. One main reason being that ... More
Learning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learningMay 20 2017Deep Reinforcement Learning (DRL) methods have performed well in an increasing numbering of high-dimensional visual decision making domains. Among all such visual decision making problems, those with discrete action spaces often tend to have underlying ... More
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural NetworksJan 31 2018Recently there has been a lot of work on pruning filters from deep convolutional neural networks (CNNs) with the intention of reducing computations. The key idea is to rank the filters based on a certain criterion (say, $l_1$-norm, average percentage ... More
SLAM-Safe Planner: Preventing Monocular SLAM Failure using Reinforcement LearningJul 26 2016Oct 17 2016Effective SLAM using a single monocular camera is highly preferred due to its simplicity. However, when compared to trajectory planning methods using depth-based SLAM, Monocular SLAM in loop does need additional considerations. One main reason being that ... More
EPOpt: Learning Robust Neural Network Policies Using Model EnsemblesOct 05 2016Oct 10 2016Sample complexity and safety are major challenges when learning policies with reinforcement learning for real-world tasks -- especially when the policies are represented using rich function approximators like deep neural networks. Model-based methods ... More
Bridge Correlational Neural Networks for Multilingual Multimodal Representation LearningOct 13 2015Jul 01 2016Recently there has been a lot of interest in learning common representations for multiple views of data. Typically, such common representations are learned using a parallel corpus between the two views (say, 1M images and their English captions). In this ... More
Studying the Plasticity in Deep Convolutional Neural Networks using Random PruningDec 26 2018Recently there has been a lot of work on pruning filters from deep convolutional neural networks (CNNs) with the intention of reducing computations.The key idea is to rank the filters based on a certain criterion (say, l1-norm) and retain only the top ... More
Improvements on Hindsight LearningSep 16 2018Nov 04 2018Sparse reward problems are one of the biggest challenges in Reinforcement Learning. Goal-directed tasks are one such sparse reward problems where a reward signal is received only when the goal is reached. One promising way to train an agent to perform ... More
ExTra: Transfer-guided ExplorationJun 27 2019In this work we present a novel approach for transfer-guided exploration in reinforcement learning that is inspired by the human tendency to leverage experiences from similar encounters in the past while navigating a new task. Given an optimal policy ... More
DyVEDeep: Dynamic Variable Effort Deep Neural NetworksApr 04 2017Deep Neural Networks (DNNs) have advanced the state-of-the-art in a variety of machine learning tasks and are deployed in increasing numbers of products and services. However, the computational requirements of training and evaluating large-scale DNNs ... More
Higher-Order threshold effects to inclusive processes in QCDMar 06 2006We present threshold enhanced QCD corrections to inclusive processes such as Deep inelastic scattering, Drell-Yan process and Higgs productions through gluon fusion and bottom quark annihilation processes using the resummed cross sections. The resummed ... More
Spectral Methods for Matrices and TensorsApr 08 2010While Spectral Methods have long been used for Principal Component Analysis, this survey focusses on work over the last 15 years with three salient features: (i) Spectral methods are useful not only for numerical problems, but also discrete optimization ... More
On Sudakov and Soft resummations in QCDDec 20 2005Dec 30 2005In this article we extract soft distribution functions for Drell-Yan and Higgs production processes using mass factorisation theorem and the perturbative results that are known upto three loop level. We find that they are maximally non-abelien. We show ... More
Gluon fragmentation function in polarised $Λ$ hyperon production: The Method of FactorisationJun 07 1996We discuss the polarised fragmentation functions of quarks and gluons in Perturbative Quantum Chromodynamics. The Altarelli-Parisi evolution equations governing these fragmentation functions are presented. We find that the first moment of the polarised ... More
Fusion Graph Convolutional NetworksMay 31 2018Sep 21 2018Semi-supervised node classification in attributed graphs, i.e., graphs with node features, involves learning to classify unlabeled nodes given a partially labeled graph. Label predictions are made by jointly modeling the node and its' neighborhood features. ... More
HOPF: Higher Order Propagation Framework for Deep Collective ClassificationMay 31 2018Nov 13 2018Given a graph where every node has certain attributes associated with it and some nodes have labels associated with them, Collective Classification (CC) is the task of assigning labels to every unlabeled node using information from the node as well as ... More
Efficient Computation of the Shapley Value for Game-Theoretic Network CentralityFeb 04 2014The Shapley value---probably the most important normative payoff division scheme in coalitional games---has recently been advocated as a useful measure of centrality in networks. However, although this approach has a variety of real-world applications ... More
Two new Probability inequalities and Concentration ResultsSep 15 2008May 21 2010Concentration results and probabilistic analysis for combinatorial problems like the TSP, MWST, graph coloring have received much attention, but generally, for i.i.d. samples (i.i.d. points in the unit square for the TSP, for example). Here, we prove ... More
The Polarised $Λ$ production in QCDJul 21 1996The $Q^2$ evolution of polarised parton fragmentation functions is discussed using Altarelli-Parisi evolution equations. The first moments of both polarised quark and gluon fragmentation functions are shown to behave in a similar fashion at very high ... More
Order $α_s(Q^2)$ QCD corrections to the polarised $e^+~e^- \to Λ~X$Jun 07 1996The importance of polarised gluons fragmenting into $\Lambda$ in the polarised $e^+ e^-$ annihilation is discussed using the Altarelli-Parisi evolution equations satisfied by the quark and gluon fragmentation functions. In this context, the polarised ... More
$A^2T$: Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sourcesOct 10 2015Sep 22 2016The ability to transfer knowledge from source tasks to a new target task can be very useful in speeding up a Reinforcement Learning agent. Such transfer has been receiving a lot of attention lately, yet the application of transfer poses two serious challenges ... More
DiGrad: Multi-Task Reinforcement Learning with Shared ActionsFeb 27 2018Most reinforcement learning algorithms are inefficient for learning multiple tasks in complex robotic systems, where different tasks share a set of actions. In such environments a compound policy may be learnt with shared neural network parameters, which ... More
Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domainOct 10 2015Apr 18 2017Transferring knowledge from prior source tasks in solving a new target task can be useful in several learning applications. The application of transfer poses two serious challenges which have not been adequately addressed. First, the agent should be able ... More
Numerical solution of perturbed Kepler problem using a split operator techniqueOct 05 2006An efficient geometric integrator is proposed for solving the perturbed Kepler motion. This method is stable and accurate over long integration time, which makes it appropriate for treating problems in astrophysics, like solar system simulations, and ... More
An Autoencoder Approach to Learning Bilingual Word RepresentationsFeb 06 2014Cross-language learning allows us to use training data from one language to build models for a different language. Many approaches to bilingual learning require that we have word-level alignment of sentences from parallel corpora. In this work we explore ... More
Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties [Extended Version]Sep 20 2017In knowledge bases such as Wikidata, it is possible to assert a large set of properties for entities, ranging from generic ones such as name and place of birth to highly profession-specific or background-specific ones such as doctoral advisor or medical ... More
Learning to Prevent Monocular SLAM Failure using Reinforcement LearningDec 23 2018Monocular SLAM refers to using a single camera to estimate robot ego motion while building a map of the environment. While Monocular SLAM is a well studied problem, automating Monocular SLAM by integrating it with trajectory planning frameworks is particularly ... More
Clustering with Spectral Norm and the k-means AlgorithmApr 11 2010There has been much progress on efficient algorithms for clustering data points generated by a mixture of $k$ probability distributions under the assumption that the means of the distributions are well-separated, i.e., the distance between the means of ... More
Finding a latent k-simplex in O(k . nnz(data)) time via Subset SmoothingApr 14 2019The core problem in many Latent Variable Models, widely used in Unsupervised Learning is to find a latent k-simplex K in Rd given perturbed points from it, many of which lie far outside the simplex. This problem was stated in [2] as an open problem. We ... More
Photon Structure Functions: Target Photon Mass Effects and QCD CorrectionsNov 08 1994We present a systematic analysis of the processes $e^+ ~e^- \rightarrow e^+ ~e^- X$ to study the polarised and unpolarised photon structure functions. The effect of target photon mass, which manifests itself as new singly polarised structure functions ... More
Hyaline: Fast and Transparent Lock-Free Memory ReclamationMay 20 2019We present a new lock-free safe memory reclamation algorithm, Hyaline, which is fast, scalable, and transparent to the underlying data structures. Due to very low contention, Hyaline is generally faster than existing approaches, including epoch-based ... More
Threshold corrections to rapidity distributions of Z and W^\pm bosons beyond N^2 LO at hadron collidersAug 13 2007Threshold enhanced perturbative QCD corrections to rapidity distributions of $Z$ and $W^\pm$ bosons at hadron colliders are presented using the Sudakov resummed cross sections at N${}^3$LO level. We have used renormalisation group invariance and the mass ... More
Unparticle physics at hadron collider via dilepton productionMay 31 2007Oct 24 2007The scale invariant unparticle physics recently proposed by Georgi could manifest at low energies as non integral number d_U of invisible particles. Unparticles if existing, could couple to the Standard Model fields and consequently affect the collider ... More
Angular distribution of Drell-Yan process at hadron colliders to NLO-QCD in models of TeV scale gravityJul 21 2005Jul 19 2006In TeV scale gravity models, for dilepton production at hadron colliders, we present the NLO-QCD corrections for the double differential cross section in the invariant mass and scattering angle. For both ADD and RS models, the quantitative impact of QCD ... More
Chemical Bonding Analysis on Amphoteric Hydrogen - Alkaline Earth Ammine BorohydridesOct 08 2017Usually the ions in solid are in the positive oxidation states or in the negative oxidation state depending upon the chemical environment. It is highly unusual for an ion having both positive as well as negative oxidation state in a particular compound. ... More
Prediction of Magnetoelectric behavior in Bi2MnTiO6Oct 03 2016We present results from ab initio calculations based on density functional theory for bismuth-based double perovskite Bi2MnTiO6. Using total energy calculation with stress and force minimization we have predicted the equilibrium crystal structure for ... More
Finding a latent k-simplex in O(k . nnz(data)) time via Subset SmoothingApr 14 2019Apr 19 2019The core problem in many Latent Variable Models, widely used in Unsupervised Learning is to find a latent k-simplex K in Rd given perturbed points from it, many of which lie far outside the simplex. This problem was stated in [2] as an open problem. We ... More
$O(α_s^2)$ Timelike Wilson Coefficients for Parton-Fragmentation Functions in Mellin SpaceApr 03 2006We calculate the Mellin moments of the $O(\alpha_s^2)$ coefficient functions for the unpolarized and polarized fragmentation functions. They can be expressed in terms of multiple finite harmonic sums of maximal weight {\sf w = 4}. Using algebraic and ... More
QCD threshold corrections to Higgs decay and to hadroproduction in $l^+l^-$ annihilationApr 30 2006We present threshold enhanced QCD corrections to the bottom quark energy distribution in Higgs boson decay and to hadroproduction in $l^+l^-$ annihilation beyond leading order in the strong coupling constant. This is achieved using the resummed decay ... More
On threshold resummation beyond leading 1-x orderFeb 16 2009Sep 30 2009We check against exact finite order three-loop results for the non-singlet F_2 and F_3 structure functions the validity of a class of momentum space ansaetze for threshold resummation at the next-to-leading order in 1-x, which generalize results previously ... More
Mellin Moments of the Next-to-next-to Leading Order Coefficient Functions for the Drell-Yan Process and Hadronic Higgs-Boson ProductionJan 19 2005Mar 21 2005We calculate the Mellin moments of the next-to-next-to leading order coefficient functions for the Drell--Yan and Higgs production cross sections. The results can be expressed in terms of multiple finite harmonic sums of maximal weight w = 4. Using algebraic ... More
Photon Structure Functions: Target Photon Mass Effects and QCD CorrectionsJun 27 1996We present a systematic analysis of the polarised and unpolarised processes $e^+ ~e^- \rightarrow e^+ ~e^- X$ in the deep inelastic limit and study the effects of target photon mass (virtuality) on the photon structure functions. The effect of target ... More
NNLO coefficient functions of Higgs and Drell--Yan cross sections in Mellin spaceJul 05 2004We calculate the Mellin moments of next-to-next-to-leading order coefficient functions of the Drell-Yan and Higgs production cross sections. The results can be expressed in term of finite harmonic sums which are maximally threefold up to weight four. ... More
QCD prerequisites for extra dimension searchesJul 27 2007For the dilepton production at hadron collider in TeV scale gravity models, inclusion of QCD corrections to NLO stabilises the cross section with respect to scale variations. The K-factors for the various distributions for the ADD and RS model at both ... More
Can Polarised Drell-Yan Shed More Light On The Proton Spin?Aug 05 1992We analyse polarised Drell-Yan process using the factorisation method and derive operator definitions for polarised parton distribution functions. We demonstrate that a factorisation analogous to that in the unpolarised Drell-Yan case holds in this process. ... More
Magnetoelectric Properties of Pb Free Bi2FeTiO6: A Theoretical InvestigationOct 11 2017The structural, electronic, magnetic and ferroelectric properties of Pb free double perovskite multiferroic Bi2FeTiO6 are investigated using density functional theory within the general gradient approximation (GGA) method. Our structural optimization ... More
Structural Phase Stability in Fluorinated Calcium HydrideOct 02 2016In order to improve the hydrogen storage properties of calcium hydride (CaH2), we have tuned its thermodynamical properties through fluorination. Using ab-initio total energy calculations based on density functional theory, the structural stability, electronic ... More
Theoretical Investigation of the Magnetoelectric Properties of Bi2NiTiO6Sep 30 2017We report the first principle investigations on the structural, electronic, magnetic and ferroelectric properties of a Pb free double perovskite multiferroic Bi2NiTiO6 using density functional theory within the general gradient approximation (GGA) and ... More
Giant magnetoelectric coupling in multiferroic PbTi$_{1-x}$V$_x$O$_{3}$ from density functional calculationsAug 01 2019The giant magnetoelectric coupling is a very rare phenomenon which has gained a lot of attention for the past few decades because of fundamental interest as well as practical applications. Here, we have successfully achieved the giant magnetoelectric ... More
Network Representation Learning: Consolidation and Renewed BearingMay 02 2019Jun 15 2019Graphs are a natural abstraction for many problems where nodes represent entities and edges represent a relationship across entities. An important area of research that has emerged over the last decade is the use of graphs as a vehicle for non-linear ... More
Network Representation Learning: Consolidation and Renewed BearingMay 02 2019Graphs are a natural abstraction for many problems where nodes represent entities and edges represent a relationship across entities. An important area of research that has emerged over the last decade is the use of graphs as a vehicle for non-linear ... More
Theoretical Investigation on the Effect of multinary Isoelectronic Substitution on TiCoSb based half-Heusler alloysAug 07 2018To understand the effect of isoelectronic substitution on thermoelectric properties of TiCoSb based half - Heusler (HH) alloys, we have systematically studied the transport properties with substitution of Zr at Ti and Bi at Sb sites. The electronic structure ... More
CoMIC: Good features for detection and matching at object boundariesDec 05 2014Feature or interest points typically use information aggregation in 2D patches which does not remain stable at object boundaries when there is object motion against a significantly varying background. Level or iso-intensity curves are much more stable ... More
Effect of multinary substitution on electronic and transport properties of TiCoSb based half-Heusler alloysOct 07 2017The electronic structures of TixZrx/2CoPbxTex, TixZrx/2Hfx/2CoPbxTex (x = 0.5), and the parent compound TiCoSb were investigated using the full potential linearized augmented plane wave method. The thermoelectric transport properties of these alloys are ... More
Search for Thermoelectrics with High Figure of Merit in half-Heusler compounds with multinary substitutionOct 03 2017In order to improve the thermoelectric performance of TiCoSb we have substituted 50% of Ti equally with Zr and Hf at Ti site and Sb with Sn and Se equally at Sb site. The electronic structure of Ti0.5Zr0.25Hf0.25CoSn0.5Se0.5 is investigated using the ... More
Mobility Study for Named Data Networking in Wireless Access NetworksJun 20 2014Information centric networking (ICN) proposes to redesign the Internet by replacing its host-centric design with information-centric design. Communication among entities is established at the naming level, with the receiver side (referred to as the Consumer) ... More
ezBFT: Decentralizing Byzantine Fault-Tolerant State Machine ReplicationApr 12 2019We present ezBFT, a novel leaderless, distributed consensus protocol capable of tolerating byzantine faults. ezBFT's main goal is to minimize the client-side latency in WAN deployments. It achieves this by (i) having no designated primary replica, and ... More
Principal Component Analysis and Higher Correlations for Distributed DataApr 10 2013Jun 29 2014We consider algorithmic problems in the setting in which the input data has been partitioned arbitrarily on many servers. The goal is to compute a function of all the data, and the bottleneck is the communication used by the algorithm. We present algorithms ... More
PDF and scale uncertainties of various DY distributions in ADD and RS models at hadron collidersApr 16 2006Sep 11 2006In the extra dimension models of ADD and RS we study the dependence of the various parton distribution functions on observable of Drell-Yan process to NLO in QCD at LHC and Tevatron energies. Uncertainties at LHC due to factorisation scales in going from ... More
Production of a KK-graviton and a Vector Boson in ADD Model via Gluon fusionNov 28 2011Dec 09 2011In the models with large extra-dimensions, we examine the production of a vector boson (\gamma / Z) in association with the Kaluza-Klein (KK) modes of the graviton via gluon fusion. At the leading order, the process takes place through quark-loop box ... More
QCD corrections up to order alpha_s^2 to polarized quark production in e^+ e^- -annihilationJun 13 2000Aug 15 2000The revised version contains two additional references i.e. [13], [14] w.r.t. to the original paper. Furthermore Eq. (33) in [11] at the end of the paragraph below (3.17) must be Eq. (33) in [10]. Misprints in the list of references are corrected.
Amphoteric behavior of Hydrogen in Bimetallic Molecular like HydridesAug 09 2018Generally hydrogen will adopt the +1, 0 or -1 oxidation state in solids depending upon the chemical environment it occupy. Typically, there are some exceptional cases in which hydrogen exhibits both anionic and cationic behavior in the same structural ... More
Transverse structure function in the factorisation methodJul 22 1996Aug 08 1996Deep Inelastic scattering experiments using transversely polarised targets yield information on the structure function $g_2$. By means of a free-field analysis, we study the operator structure of $g_2$ and demonstrate the need for retaining the twist ... More
Some Properties of Accretive Operators in Linear 2-Normed SpacesJul 09 2017In this paper we discuss some properties of resolvents of an accretive operator in linear 2-normed spaces, focusing on the concept of contraction mapping and the unique fixed point of contraction mappings in linear 2- normed spaces. Also, we establish ... More
A provable SVD-based algorithm for learning topics in dominant admixture corpusOct 26 2014Nov 04 2014Topic models, such as Latent Dirichlet Allocation (LDA), posit that documents are drawn from admixtures of distributions over words, known as topics. The inference problem of recovering topics from admixtures, is NP-hard. Assuming separability, a strong ... More