A Randomized Algorithm for Large Scale Support Vector Learning

We propose a randomized algorithm for large scale SVM learning which solves the problem by iterating over random subsets of the data. Crucial to the algorithm for scalability is the size of the subsets chosen. In the context of text classification we show that, by using ideas from random projections, a sample size of O(log n) can be used to obtain a solution which is close to the optimal with a high probability. Experiments done on synthetic and real life data sets demonstrate that the algorithm scales up SVM learners, without loss in accuracy. 1

Focussed Crawling with large scale Ordinal Regression Solvers

In this paper we propose a novel, scalable, clustering based Ordinal Regression formulation, which is an instance of a Second Order Cone Program (SOCP) with one Second Order Cone (SOC) constraint. The main contribution of the paper is a fast algorithm, CB-OR, which solves the proposed formulation more eficiently than general purpose solvers. Another main contribution of the paper is to pose the problem of focused crawling as a large scale Ordinal Regression problem and solve using the proposed CB-OR. Focused crawling is an efficient mechanism for discovering resources of interest on the web. Posing the problem of focused crawling as an Ordinal Regression problem avoids the need for a negative class and topic hierarchy, which are the main drawbacks of the existing focused crawling methods. Experiments on large synthetic and benchmark datasets show the scalability of CB-OR. Experiments also show that the proposed focused crawler outperforms the state-of-the-art.

Filtered density function for large eddy simulation of turbulent reacting flows

A methodology termed the “filtered density function” (FDF) is developed and implemented for large eddy simulation (LES) of chemically reacting turbulent flows. In this methodology, the effects of the unresolved scalar fluctuations are taken into account by considering the probability density function (PDF) of subgrid scale (SGS) scalar quantities. A transport equation is derived for the FDF in which the effect of chemical reactions appears in a closed form. The influences of scalar mixing and convection within the subgrid are modeled. The FDF transport equation is solved numerically via a Lagrangian Monte Carlo scheme in which the solutions of the equivalent stochastic differential equations (SDEs) are obtained. These solutions preserve the Itô-Gikhman nature of the SDEs. The consistency of the FDF approach, the convergence of its Monte Carlo solution and the performance of the closures employed in the FDF transport equation are assessed by comparisons with results obtained by direct numerical simulation (DNS) and by conventional LES procedures in which the first two SGS scalar moments are obtained by a finite difference method (LES-FD). These comparative assessments are conducted by implementations of all three schemes (FDF, DNS and LES-FD) in a temporally developing mixing layer and a spatially developing planar jet under both non-reacting and reacting conditions. In non-reacting flows, the Monte Carlo solution of the FDF yields results similar to those via LES-FD. The advantage of the FDF is demonstrated by its use in reacting flows. In the absence of a closure for the SGS scalar fluctuations, the LES-FD results are significantly different from those based on DNS. The FDF results show a much closer agreement with filtered DNS results. © 1998 American Institute of Physics.

A Scalable Low Power Issue Queue for Large Instruction Window Processors

Large instruction windows and issue queues are key to exploiting greater instruction level parallelism in out-of-order superscalar processors. However, the cycle time and energy consumption of conventional large monolithic issue queues are high. Previous efforts to reduce cycle time segment the issue queue and pipeline wakeup. Unfortunately, this results in significant IPC loss. Other proposals which address energy efficiency issues by avoiding only the unnecessary tag-comparisons do not reduce broadcasts. These schemes also increase the issue latency.To address both these issues comprehensively, we propose the Scalable Lowpower Issue Queue (SLIQ). SLIQ augments a pipelined issue queue with direct indexing to mitigate the problem of delayed wakeups while reducing the cycle time. Also, the SLIQ design naturally leads to significant energy savings by reducing both the number of tag broadcasts and comparisons required.A 2 segment SLIQ incurs an average IPC loss of 0.2% over the entire SPEC CPU2000 suite, while achieving a 25.2% reduction in issue latency when compared to a monolithic 128-entry issue queue for an 8-wide superscalar processor. An 8 segment SLIQ improves scalability by reducing the issue latency by 38.3% while incurring an IPC loss of only 2.3%. Further, the 8 segment SLIQ significantly reduces the energy consumption and energy-delay product by 48.3% and 67.4% respectively on average.

Clustering Based Large Margin Classification: A Scalable Approach using SOCP Formulation

This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture distributions, where each component of the mixture has a spherical covariance, the second order statistics of the components can be estimated efficiently using clustering algorithms like BIRCH. For each cluster, the second order moments are used to derive a second order cone constraint via a Chebyshev-Cantelli inequality. This constraint ensures that any data point in the cluster is classified correctly with a high probability. This leads to a large margin SOCP formulation whose size depends on the number of clusters rather than the number of training data points. Hence, the proposed formulation scales well for large datasets when compared to the state-of-the-art classifiers, Support Vector Machines (SVMs). Experiments on real world and synthetic datasets show that the proposed algorithm outperforms SVM solvers in terms of training time and achieves similar accuracies.

On the cut‐on frequencies of a large round duct with azimuthal as well as radial partitions

This letter deals with a three‐dimensional analysis of circular sectors and annular segments resulting from the partitioning of a round (cylindrical) duct for use in an active noise control system. The relevant frequency equations are derived for stationary medium and solved numerically to arrive at the cut‐on frequencies of the first few modes. The resultant table indicates among other things that azimuthal partitioning does not raise the cutoff frequency (the smallest cut‐on frequency) beyond a particular value, and that radial partitioning is counterproductive in that respect.

The fluorescence of Nd3+ in lead borate and bismuth borate glasses with large stimulated emission cross section

The stimulated emission cross section σp for the 1060 nm transition of Nd3+ in lead borate and bismuth borate glasses has been determined from fluorescence measurements. The compositional dependence of σp, which has been evaluated using radiative transition probability, refractive index of the host glass, effective fluorescence linewidth, and position of the band, with PbO/Bi2O3 content is investigated. The σp values of the 1060 nm band of Nd3+ for lead borate and bismuth borate glasses are found to be in the range 2.6–5.7×10−20 cm2 at 298 K and 3.0–6.3×10−20 cm2 at 4.2 K. The σp values are comparatively large suggesting the possible utilization of these materials in laser applications.

Low-Complexity Detection in Large-Dimension MIMO-ISI Channels Using Graphical Models

In this paper, we deal with low-complexity near-optimal detection/equalization in large-dimension multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels using message passing on graphical models. A key contribution in the paper is the demonstration that near-optimal performance in MIMO-ISI channels with large dimensions can be achieved at low complexities through simple yet effective simplifications/approximations, although the graphical models that represent MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1) use of Markov random field (MRF)-based graphical model with pairwise interaction, in conjunction with message damping, and 2) use of factor graph (FG)-based graphical model with Gaussian approximation of interference (GAI). The per-symbol complexities are O(K(2)n(t)(2)) and O(Kn(t)) for the MRF and the FG with GAI approaches, respectively, where K and n(t) denote the number of channel uses per frame, and number of transmit antennas, respectively. These low-complexities are quite attractive for large dimensions, i.e., for large Kn(t). From a performance perspective, these algorithms are even more interesting in large-dimensions since they achieve increasingly closer to optimum detection performance for increasing Kn(t). Also, we show that these message passing algorithms can be used in an iterative manner with local neighborhood search algorithms to improve the reliability/performance of M-QAM symbol detection.

Large reduction of leakage current by graded-layer La doping in (Ba0.5, Sr0.5)TiO3 thin films

A large reduction in the leakage current behavior in (Ba, Sr)TiO3 (BST) thin films was observed by graded-layer donor doping. The graded doping was achieved by introducing La-doped BST layers in the grown BST films. The films showed a large decrease (about six orders of magnitude) in the leakage current in comparison to undoped films at an electric field of 100 kV/cm. The large decrease in leakage current was attributed to the formation of highly resistive layers, originating from compensating defect chemistry involved for La-doped films grown in oxidizing environment. Temperature-dependent leakage-current behavior was studied to investigate the conduction mechanism and explanations of the results were sought from Poole–Frenkel conduction mechanism.

Decentralized dynamic compensators for large multivariable systems

In this paper, we consider the synthesis of decentralized dynamic compensators for large systems. The eliminant approach is used to obtain sufficient conditions for the existence of proper, stable, decentralized observer-controllers for stabilizing a large system. An illustrative example is given.

Fluid Mechanics of Aquatic Locomotion at Large Reynolds Numbers

Abstract | There exist a huge range of fish species besides other aquatic organisms like squids and salps that locomote in water at large Reynolds numbers, a regime of flow where inertial forces dominate viscous forces. In the present review, we discuss the fluid mechanics governing the locomotion of such organisms. Most fishes propel themselves by periodic undulatory motions of the body and tail, and the typical classification of their swimming modes is based on the fraction of their body that undergoes such undulatory motions. In the angulliform mode, or the eel type, the entire body undergoes undulatory motions in the form of a travelling wave that goes from head to tail, while in the other extreme case, the thunniform mode, only the rear tail (caudal fin) undergoes lateral oscillations. The thunniform mode of swimming is essentially based on the lift force generated by the airfoil like crosssection of the fish tail as it moves laterally through the water, while the anguilliform mode may be understood using the “reactive theory” of Lighthill. In pulsed jet propulsion, adopted by squids and salps, there are two components to the thrust; the first due to the familiar ejection of momentum and the other due to an over-pressure at the exit plane caused by the unsteadiness of the jet. The flow immediately downstream of the body in all three modes consists of vortex rings; the differentiating point being the vastly different orientations of the vortex rings. However, since all the bodies are self-propelling, the thrust force must be equal to the drag force (at steady speed), implying no net force on the body, and hence the wake or flow downstream must be momentumless. For such bodies, where there is no net force, it is difficult to directly define a propulsion efficiency, although it is possible to use some other very different measures like “cost of transportation” to broadly judge performance.