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A cross-correlation-based estimate of the galaxy luminosity function
We extend existing methods for using cross-correlations to derive redshift distributions for photometric galaxies, without using photometric redshifts. The model presented in this paper simultaneously yields highly accurate and unbiased redshift distributions and, for the first time, redshift-dependent luminosity fun...
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A Novel Partitioning Method for Accelerating the Block Cimmino Algorithm
We propose a novel block-row partitioning method in order to improve the convergence rate of the block Cimmino algorithm for solving general sparse linear systems of equations. The convergence rate of the block Cimmino algorithm depends on the orthogonality among the block rows obtained by the partitioning method. Th...
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Visualized Insights into the Optimization Landscape of Fully Convolutional Networks
Many image processing tasks involve image-to-image mapping, which can be addressed well by fully convolutional networks (FCN) without any heavy preprocessing. Although empirically designing and training FCNs can achieve satisfactory results, reasons for the improvement in performance are slightly ambiguous. Our study...
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Exact upper and lower bounds on the misclassification probability
Exact lower and upper bounds on the best possible misclassification probability for a finite number of classes are obtained in terms of the total variation norms of the differences between the sub-distributions over the classes. These bounds are compared with the exact bounds in terms of the conditional entropy obtai...
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BB-Graph: A Subgraph Isomorphism Algorithm for Efficiently Querying Big Graph Databases
The big graph database model provides strong modeling for complex applications and efficient querying. However, it is still a big challenge to find all exact matches of a query graph in a big graph database, which is known as the subgraph isomorphism problem. The current subgraph isomorphism approaches are built on U...
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Analytic solutions of the Madelung equation
We present analytic self-similar solutions for the one, two and three dimensional Madelung hydrodynamical equation for a free particle. There is a direct connection between the zeros of the Madelung fluid density and the magnitude of the quantum potential.
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Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders
We employ unsupervised machine learning techniques to learn latent parameters which best describe states of the two-dimensional Ising model and the three-dimensional XY model. These methods range from principal component analysis to artificial neural network based variational autoencoders. The states are sampled usin...
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A novel online scheduling protocol for energy-efficient TWDM-OLT design
Design of energy-efficient access networks has emerged as an important area of research, since access networks consume $80-90\%$ of the overall Internet power consumption. TWDM-PON is envisaged to be one of the widely accepted future access technologies. TWDM-PON offers an additional opportunity to save energy at the...
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Machines and Algorithms
I discuss the evolution of computer architectures with a focus on QCD and with reference to the interplay between architecture, engineering, data motion and algorithms. New architectures are discussed and recent performance results are displayed. I also review recent progress in multilevel solver and integation algor...
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Large Margin Learning in Set to Set Similarity Comparison for Person Re-identification
Person re-identification (Re-ID) aims at matching images of the same person across disjoint camera views, which is a challenging problem in multimedia analysis, multimedia editing and content-based media retrieval communities. The major challenge lies in how to preserve similarity of the same person across video foot...
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Scheduling Constraint Based Abstraction Refinement for Multi-Threaded Program Verification
Bounded model checking is among the most efficient techniques for the automatic verification of concurrent programs. However, encoding all possible interleavings often requires a huge and complex formula, which significantly limits the salability. This paper proposes a novel and efficient abstraction refinement metho...
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The braid group for a quiver with superpotential
We survey and compare various generalizations of braid groups for quivers with superpotential and focus on the cluster braid groups, which are introduced in a joint work with A.~King. Our motivations come from the study of cluster algebras, Calabi-Yau categories and Bridgeland stability conditions.
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The infinitesimal characters of discrete series for real spherical spaces
Let $Z=G/H$ be the homogeneous space of a real reductive group and a unimodular real spherical subgroup, and consider the regular representation of $G$ on $L^2(Z)$. It is shown that all representations of the discrete series, that is, the irreducible subrepresentations of $L^2(Z)$, have infinitesimal characters which...
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Coincidence point results involving a generalized class of simulation functions
The purpose of this work is to introduce a general class of $C_G$-simulation functions and obtained some new coincidence and common fixed points results in metric spaces. Some useful examples are presented to illustrate our theorems. Results obtained in this paper extend, generalize and unify some well known fixed an...
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A Simulated Cyberattack on Twitter: Assessing Partisan Vulnerability to Spear Phishing and Disinformation ahead of the 2018 U.S. Midterm Elections
State-sponsored "bad actors" increasingly weaponize social media platforms to launch cyberattacks and disinformation campaigns during elections. Social media companies, due to their rapid growth and scale, struggle to prevent the weaponization of their platforms. This study conducts an automated spear phishing and di...
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Asteroid mass estimation using Markov-chain Monte Carlo
Estimates for asteroid masses are based on their gravitational perturbations on the orbits of other objects such as Mars, spacecraft, or other asteroids and/or their satellites. In the case of asteroid-asteroid perturbations, this leads to an inverse problem in at least 13 dimensions where the aim is to derive the ma...
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Asymptotic Properties of the Maximum Likelihood Estimator in Regime Switching Econometric Models
Markov regime switching models have been widely used in numerous empirical applications in economics and finance. However, the asymptotic distribution of the maximum likelihood estimator (MLE) has not been proven for some empirically popular Markov regime switching models. In particular, the asymptotic distribution o...
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Fleet management for autonomous vehicles: Online PDP under special constraints
The VIPAFLEET project consists in developing models and algorithms for man- aging a fleet of Individual Public Autonomous Vehicles (VIPA). Hereby, we consider a fleet of cars distributed at specified stations in an industrial area to supply internal transportation, where the cars can be used in different modes of cir...
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Bayesian Model Selection for Misspecified Models in Linear Regression
While the Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC) are powerful tools for model selection in linear regression, they are built on different prior assumptions and thereby apply to different data generation scenarios. We show that in the finite-dimensional case their respective assump...
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Near-optimal sample complexity for convex tensor completion
We analyze low rank tensor completion (TC) using noisy measurements of a subset of the tensor. Assuming a rank-$r$, order-$d$, $N \times N \times \cdots \times N$ tensor where $r=O(1)$, the best sampling complexity that was achieved is $O(N^{\frac{d}{2}})$, which is obtained by solving a tensor nuclear-norm minimizat...
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Conditional Lower Bounds for Space/Time Tradeoffs
In recent years much effort has been concentrated towards achieving polynomial time lower bounds on algorithms for solving various well-known problems. A useful technique for showing such lower bounds is to prove them conditionally based on well-studied hardness assumptions such as 3SUM, APSP, SETH, etc. This line of...
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Full Quantification of Left Ventricle via Deep Multitask Learning Network Respecting Intra- and Inter-Task Relatedness
Cardiac left ventricle (LV) quantification is among the most clinically important tasks for identification and diagnosis of cardiac diseases, yet still a challenge due to the high variability of cardiac structure and the complexity of temporal dynamics. Full quantification, i.e., to simultaneously quantify all LV ind...
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On sparsity and power-law properties of graphs based on exchangeable point processes
This paper investigates properties of the class of graphs based on exchangeable point processes. We provide asymptotic expressions for the number of edges, number of nodes and degree distributions, identifying four regimes: a dense regime, a sparse, almost dense regime, a sparse regime with power-law behavior, and an...
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Information transmission on hybrid networks
Many real-world communication networks often have hybrid nature with both fixed nodes and moving modes, such as the mobile phone networks mainly composed of fixed base stations and mobile phones. In this paper, we discuss the information transmission process on the hybrid networks with both fixed and mobile nodes. Th...
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Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN
We propose a novel technique to make neural network robust to adversarial examples using a generative adversarial network. We alternately train both classifier and generator networks. The generator network generates an adversarial perturbation that can easily fool the classifier network by using a gradient of each im...
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Bad Primes in Computational Algebraic Geometry
Computations over the rational numbers often suffer from intermediate coefficient swell. One solution to this problem is to apply the given algorithm modulo a number of primes and then lift the modular results to the rationals. This method is guaranteed to work if we use a sufficiently large set of good primes. In ma...
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Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems. In this paper, we consider knowledge graphs as the source of side in...
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On Consistency of Graph-based Semi-supervised Learning
Graph-based semi-supervised learning is one of the most popular methods in machine learning. Some of its theoretical properties such as bounds for the generalization error and the convergence of the graph Laplacian regularizer have been studied in computer science and statistics literatures. However, a fundamental st...
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Modeling Label Ambiguity for Neural List-Wise Learning to Rank
List-wise learning to rank methods are considered to be the state-of-the-art. One of the major problems with these methods is that the ambiguous nature of relevance labels in learning to rank data is ignored. Ambiguity of relevance labels refers to the phenomenon that multiple documents may be assigned the same relev...
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Whitehead torsion of inertial h-cobordisms
We study the Whitehead torsions of inertial h-cobordisms, and identify various types representing a nested sequence of subsets of the Whitehead group. A number of examples are given to show that these subsets are all different in general.
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Propagation from Deceptive News Sources: Who Shares, How Much, How Evenly, and How Quickly?
As people rely on social media as their primary sources of news, the spread of misinformation has become a significant concern. In this large-scale study of news in social media we analyze eleven million posts and investigate propagation behavior of users that directly interact with news accounts identified as spread...
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Self-protected nanoscale thermometry based on spin defects in silicon carbide
Quantum sensors with solid state electron spins have attracted considerable interest due to their nanoscale spatial resolution.A critical requirement is to suppress the environment noise of the solid state spin sensor.Here we demonstrate a nanoscale thermometer based on silicon carbide (SiC) electron spins.We experim...
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Robot Composite Learning and the Nunchaku Flipping Challenge
Advanced motor skills are essential for robots to physically coexist with humans. Much research on robot dynamics and control has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learni...
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Querying Best Paths in Graph Databases
Querying graph databases has recently received much attention. We propose a new approach to this problem, which balances competing goals of expressive power, language clarity and computational complexity. A distinctive feature of our approach is the ability to express properties of minimal (e.g. shortest) and maximal...
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Communication Complexity of Correlated Equilibrium in Two-Player Games
We show a communication complexity lower bound for finding a correlated equilibrium of a two-player game. More precisely, we define a two-player $N \times N$ game called the 2-cycle game and show that the randomized communication complexity of finding a 1/poly($N$)-approximate correlated equilibrium of the 2-cycle ga...
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On the computability of graph Turing machines
We consider graph Turing machines, a model of parallel computation on a graph, in which each vertex is only capable of performing one of a finite number of operations. This model of computation is a natural generalization of several well-studied notions of computation, including ordinary Turing machines, cellular aut...
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SCRank: Spammer and Celebrity Ranking in Directed Social Networks
Many online social networks allow directed edges: Alice can unilaterally add an "edge" to Bob, typically indicating interest in Bob or Bob's content, without Bob's permission or reciprocation. In directed social networks we observe the rise of two distinctive classes of users: celebrities who accrue unreciprocated in...
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Taylor series and twisting-index invariants of coupled spin-oscillators
About six years ago, semitoric systems on 4-dimensional manifolds were classified by Pelayo & Vu Ngoc by means of five invariants. A standard example of such a system is the coupled spin-oscillator on $\mathbb{S}^2 \times \mathbb{R}^2$. Calculations of three of the five semitoric invariants of this system (namely the...
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Optimal DoF region of the K-User MISO BC with Partial CSIT
We consider the $K$-User Multiple-Input-Single-Output (MISO) Broadcast Channel (BC) where the transmitter, equipped with $M$ antennas, serves $K$ users, with $K \leq M$. The transmitter has access to a partial channel state information of the users. This is modelled by letting the variance of the Channel State Inform...
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Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows
We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a macroscopic continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations wh...
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Collective search with finite perception: transient dynamics and search efficiency
Motile organisms often use finite spatial perception of their surroundings to navigate and search their habitats. Yet standard models of search are usually based on purely local sensory information. To model how a finite perceptual horizon affects ecological search, we propose a framework for optimal navigation that ...
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The first moment of cusp form L-functions in weight aspect on average
We study the asymptotic behaviour of the twisted first moment of central $L$-values associated to cusp forms in weight aspect on average. Our estimate of the error term allows extending the logarithmic length of mollifier $\Delta$ up to 2. The best previously known result, due to Iwaniec and Sarnak, was $\Delta<1$. T...
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Analyzing Boltzmann Samplers for Bose-Einstein Condensates with Dirichlet Generating Functions
Boltzmann sampling is commonly used to uniformly sample objects of a particular size from large combinatorial sets. For this technique to be effective, one needs to prove that (1) the sampling procedure is efficient and (2) objects of the desired size are generated with sufficiently high probability. We use this appr...
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On Invariant Random Subgroups of Block-Diagonal Limits of Symmetric Groups
We classify the ergodic invariant random subgroups of block-diagonal limits of symmetric groups in the cases when the groups are simple and the associated dimension groups have finite dimensional state spaces. These block-diagonal limits arise as the transformation groups (full groups) of Bratteli diagrams that prese...
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Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
Sparse Subspace Clustering (SSC) is a popular unsupervised machine learning method for clustering data lying close to an unknown union of low-dimensional linear subspaces; a problem with numerous applications in pattern recognition and computer vision. Even though the behavior of SSC for complete data is by now well-...
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On certain geometric properties in Banach spaces of vector-valued functions
We consider a certain type of geometric properties of Banach spaces, which includes for instance octahedrality, almost squareness, lushness and the Daugavet property. For this type of properties, we obtain a general reduction theorem, which, roughly speaking, states the following: if the property in question is stabl...
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Social Media Analysis based on Semanticity of Streaming and Batch Data
Languages shared by people differ in different regions based on their accents, pronunciation and word usages. In this era sharing of language takes place mainly through social media and blogs. Every second swing of such a micro posts exist which induces the need of processing those micro posts, in-order to extract kn...
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Chiral Topological Superconductors Enhanced by Long-Range Interactions
We study the phase diagram and edge states of a two-dimensional p-wave superconductor with long-range hopping and pairing amplitudes. New topological phases and quasiparticles different from the usual short-range model are obtained. When both hopping and pairing terms decay with the same exponent, one of the topologi...
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An Algebraic Glimpse at Bunched Implications and Separation Logic
We overview the logic of Bunched Implications (BI) and Separation Logic (SL) from a perspective inspired by Hiroakira Ono's algebraic approach to substructural logics. We propose generalized BI algebras (GBI-algebras) as a common framework for algebras arising via "declarative resource reading", intuitionistic genera...
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The adapted hyper-Kähler structure on the crown domain
Let $\,\Xi\,$ be the crown domain associated with a non-compact irreducible hermitian symmetric space $\,G/K$. We give an explicit description of the unique $\,G$-invariant adapted hyper-Kähler structure on $\,\Xi$,$\ $i.$\,$e.$\ $compatible with the adapted complex structure $\,J_{ad}\,$ and with the $\,G$-invariant...
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Exact traveling wave solutions of 1D model of cancer invasion
In this paper we consider the continuous mathematical model of tumour growth and invasion based on the model introduced by Anderson, Chaplain et al. \cite{Anderson&Chaplain2000}, for the case of one space dimension. The model consists of a system of three coupled nonlinear reaction-diffusion-taxis partial differentia...
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On purity theorem of Lusztig's perverse sheaves
Let $Q$ be a finite quiver without loops and $\mathcal{Q}_{\alpha}$ be the Lusztig category for any dimension vector $\alpha$. The purpose of this paper is to prove that all Frobenius eigenvalues of the $i$-th cohomology $\mathcal{H}^i(\mathcal{L})|_x$ for a simple perverse sheaf $\mathcal{L}\in \mathcal{Q}_{\alpha}$...
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Abstract Interpretation using a Language of Symbolic Approximation
The traditional abstract domain framework for imperative programs suffers from several shortcomings; in particular it does not allow precise symbolic abstractions. To solve these problems, we propose a new abstract interpretation framework, based on symbolic expressions used both as an abstraction of the program, and...
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The Integral Transform of N.I.Akhiezer
We study the integral transform which appeared in a different form in Akhiezer's textbook "Lectures on Integral Transforms".
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Quantitative CBA: Small and Comprehensible Association Rule Classification Models
Quantitative CBA is a postprocessing algorithm for association rule classification algorithm CBA (Liu et al, 1998). QCBA uses original, undiscretized numerical attributes to optimize the discovered association rules, refining the boundaries of literals in the antecedent of the rules produced by CBA. Some rules as wel...
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Quermassintegral preserving curvature flow in Hyperbolic space
We consider the quermassintegral preserving flow of closed \emph{h-convex} hypersurfaces in hyperbolic space with the speed given by any positive power of a smooth symmetric, strictly increasing, and homogeneous of degree one function $f$ of the principal curvatures which is inverse concave and has dual $f_*$ approac...
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Cloaking for a quasi-linear elliptic partial differential equation
In this article we consider cloaking for a quasi-linear elliptic partial differential equation of divergence type defined on a bounded domain in $\mathbb{R}^N$ for $N=2,3$. We show that a perfect cloak can be obtained via a singular change of variables scheme and an approximate cloak can be achieved via a regular cha...
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Good Arm Identification via Bandit Feedback
We consider a novel stochastic multi-armed bandit problem called {\em good arm identification} (GAI), where a good arm is defined as an arm with expected reward greater than or equal to a given threshold. GAI is a pure-exploration problem that a single agent repeats a process of outputting an arm as soon as it is ide...
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Learning compressed representations of blood samples time series with missing data
Clinical measurements collected over time are naturally represented as multivariate time series (MTS), which often contain missing data. An autoencoder can learn low dimensional vectorial representations of MTS that preserve important data characteristics, but cannot deal explicitly with missing data. In this work, w...
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Fuzzy Galois connections on fuzzy sets
In fairly elementary terms this paper presents how the theory of preordered fuzzy sets, more precisely quantale-valued preorders on quantale-valued fuzzy sets, is established under the guidance of enriched category theory. Motivated by several key results from the theory of quantaloid-enriched categories, this paper ...
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QWIRE Practice: Formal Verification of Quantum Circuits in Coq
We describe an embedding of the QWIRE quantum circuit language in the Coq proof assistant. This allows programmers to write quantum circuits using high-level abstractions and to prove properties of those circuits using Coq's theorem proving features. The implementation uses higher-order abstract syntax to represent v...
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The cost of fairness in classification
We study the problem of learning classifiers with a fairness constraint, with three main contributions towards the goal of quantifying the problem's inherent tradeoffs. First, we relate two existing fairness measures to cost-sensitive risks. Second, we show that for cost-sensitive classification and fairness measures...
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The algebraic structure of cut Feynman integrals and the diagrammatic coaction
We study the algebraic and analytic structure of Feynman integrals by proposing an operation that maps an integral into pairs of integrals obtained from a master integrand and a corresponding master contour. This operation is a coaction. It reduces to the known coaction on multiple polylogarithms, but applies more ge...
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Implementing universal nonadiabatic holonomic quantum gates with transmons
Geometric phases are well known to be noise-resilient in quantum evolutions/operations. Holonomic quantum gates provide us with a robust way towards universal quantum computation, as these quantum gates are actually induced by nonabelian geometric phases. Here we propose and elaborate how to efficiently implement uni...
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Fine cophasing of segmented aperture telescopes with ZELDA, a Zernike wavefront sensor in the diffraction-limited regime
Segmented aperture telescopes require an alignment procedure with successive steps from coarse alignment to monitoring process in order to provide very high optical quality images for stringent science operations such as exoplanet imaging. The final step, referred to as fine phasing, calls for a high sensitivity wave...
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Why Pay More When You Can Pay Less: A Joint Learning Framework for Active Feature Acquisition and Classification
We consider the problem of active feature acquisition, where we sequentially select the subset of features in order to achieve the maximum prediction performance in the most cost-effective way. In this work, we formulate this active feature acquisition problem as a reinforcement learning problem, and provide a novel ...
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The Hasse Norm Principle For Biquadratic Extensions
We give an asymptotic formula for the number of biquadratic extensions of the rationals of bounded discriminant that fail the Hasse norm principle.
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Static vs Adaptive Strategies for Optimal Execution with Signals
We consider an optimal execution problem in which a trader is looking at a short-term price predictive signal while trading. In the case where the trader is creating an instantaneous market impact, we show that transactions costs resulting from the optimal adaptive strategy are substantially lower than the correspond...
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New descriptions of the weighted Reed-Muller codes and the homogeneous Reed-Muller codes
We give a description of the weighted Reed-Muller codes over a prime field in a modular algebra. A description of the homogeneous Reed-Muller codes in the same ambient space is presented for the binary case. A decoding procedure using the Landrock-Manz method is developed.
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Criteria for the Absence and Existence of Bounded Solutions at the Threshold Frequency in a Junction of Quantum Waveguides
In the junction $\Omega$ of several semi-infinite cylindrical waveguides we consider the Dirichlet Laplacian whose continuous spectrum is the ray $[\lambda_\dagger, +\infty)$ with a positive cut-off value $\lambda_\dagger$. We give two different criteria for the threshold resonance generated by nontrivial bounded sol...
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Stochastic Feedback Control of Systems with Unknown Nonlinear Dynamics
This paper studies the stochastic optimal control problem for systems with unknown dynamics. First, an open-loop deterministic trajectory optimization problem is solved without knowing the explicit form of the dynamical system. Next, a Linear Quadratic Gaussian (LQG) controller is designed for the nominal trajectory-...
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Micrometer-Sized Water Ice Particles for Planetary Science Experiments: Influence of Surface Structure on Collisional Properties
Models and observations suggest that ice-particle aggregation at and beyond the snowline dominates the earliest stages of planet-formation, which therefore is subject to many laboratory studies. However, the pressure-temperature gradients in proto-planetary disks mean that the ices are constantly processed, undergoin...
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The splashback radius of halos from particle dynamics. II. Dependence on mass, accretion rate, redshift, and cosmology
The splashback radius $R_{\rm sp}$, the apocentric radius of particles on their first orbit after falling into a dark matter halo, has recently been suggested as a physically motivated halo boundary that separates accreting from orbiting material. Using the SPARTA code presented in Paper I, we analyze the orbits of b...
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Empirical Evaluation of Parallel Training Algorithms on Acoustic Modeling
Deep learning models (DLMs) are state-of-the-art techniques in speech recognition. However, training good DLMs can be time consuming especially for production-size models and corpora. Although several parallel training algorithms have been proposed to improve training efficiency, there is no clear guidance on which o...
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Distributed Impedance Control of Latency-Prone Robotic Systems with Series Elastic Actuation
Robotic systems are increasingly relying on distributed feedback controllers to tackle complex and latency-prone sensing and decision problems. These demands come at the cost of a growing computational burden and, as a result, larger controller latencies. To maximize robustness to mechanical disturbances and achieve ...
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Simulation Methods for Stochastic Storage Problems: A Statistical Learning Perspective
We consider solution of stochastic storage problems through regression Monte Carlo (RMC) methods. Taking a statistical learning perspective, we develop the dynamic emulation algorithm (DEA) that unifies the different existing approaches in a single modular template. We then investigate the two central aspects of regr...
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Flashes of Hidden Worlds at Colliders
(This is a general physics level overview article about hidden sectors, and how they motivate searches for long-lived particles. Intended for publication in Physics Today.) Searches for new physics at the Large Hadron Collider have so far come up empty, but we just might not be looking in the right place. Spectacular...
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Espresso: Brewing Java For More Non-Volatility with Non-volatile Memory
Fast, byte-addressable non-volatile memory (NVM) embraces both near-DRAM latency and disk-like persistence, which has generated considerable interests to revolutionize system software stack and programming models. However, it is less understood how NVM can be combined with managed runtime like Java virtual machine (J...
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Multimodal Machine Learning: A Survey and Taxonomy
Our experience of the world is multimodal - we see objects, hear sounds, feel texture, smell odors, and taste flavors. Modality refers to the way in which something happens or is experienced and a research problem is characterized as multimodal when it includes multiple such modalities. In order for Artificial Intell...
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The Motivic Cofiber of $τ$
Consider the Tate twist $\tau \in H^{0,1}(S^{0,0})$ in the mod 2 cohomology of the motivic sphere. After 2-completion, the motivic Adams spectral sequence realizes this element as a map $\tau \colon S^{0,-1} \to S^{0,0}$, with cofiber $C\tau$. We show that this motivic 2-cell complex can be endowed with a unique $E_{...
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EEG machine learning with Higuchi fractal dimension and Sample Entropy as features for successful detection of depression
Reliable diagnosis of depressive disorder is essential for both optimal treatment and prevention of fatal outcomes. In this study, we aimed to elucidate the effectiveness of two non-linear measures, Higuchi Fractal Dimension (HFD) and Sample Entropy (SampEn), in detecting depressive disorders when applied on EEG. HFD...
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On Microtargeting Socially Divisive Ads: A Case Study of Russia-Linked Ad Campaigns on Facebook
Targeted advertising is meant to improve the efficiency of matching advertisers to their customers. However, targeted advertising can also be abused by malicious advertisers to efficiently reach people susceptible to false stories, stoke grievances, and incite social conflict. Since targeted ads are not seen by non-t...
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On Helmholtz free energy for finite abstract simplicial complexes
We prove a Gauss-Bonnet formula X(G) = sum_x K(x), where K(x)=(-1)^dim(x) (1-X(S(x))) is a curvature of a vertex x with unit sphere S(x) in the Barycentric refinement G1 of a simplicial complex G. K(x) is dual to (-1)^dim(x) for which Gauss-Bonnet is the definition of Euler characteristic X. Because the connection La...
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Global Patterns of Synchronization in Human Communications
Social media are transforming global communication and coordination. The data derived from social media can reveal patterns of human behavior at all levels and scales of society. Using geolocated Twitter data, we have quantified collective behaviors across multiple scales, ranging from the commutes of individuals, to...
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On the predictability of infectious disease outbreaks
Infectious disease outbreaks recapitulate biology: they emerge from the multi-level interaction of hosts, pathogens, and their shared environment. As a result, predicting when, where, and how far diseases will spread requires a complex systems approach to modeling. Recent studies have demonstrated that predicting dif...
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Multi-Player Bandits Revisited
Multi-player Multi-Armed Bandits (MAB) have been extensively studied in the literature, motivated by applications to Cognitive Radio systems. Driven by such applications as well, we motivate the introduction of several levels of feedback for multi-player MAB algorithms. Most existing work assume that sensing informat...
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Model Averaging for Generalized Linear Model with Covariates that are Missing completely at Random
In this paper, we consider the estimation of generalized linear models with covariates that are missing completely at random. We propose a model averaging estimation method and prove that the corresponding model averaging estimator is asymptotically optimal under certain assumptions. Simulaiton results illustrate tha...
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Demonstration of the length stability requirements for ALPS II with a high finesse 9.2m cavity
Light-shining-through-a-wall experiments represent a new experimental approach in the search for undiscovered elementary particles not accessible with accelerator based experiments. The next generation of these experiments, such as ALPS~II, require high finesse, long baseline optical cavities with fast length control...
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Shrub-depth: Capturing Height of Dense Graphs
The recent increase of interest in the graph invariant called tree-depth and in its applications in algorithms and logic on graphs led to a natural question: is there an analogously useful "depth" notion also for dense graphs (say; one which is stable under graph complementation)? To this end, in a 2012 conference pa...
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Detecting Statistical Interactions from Neural Network Weights
Interpreting neural networks is a crucial and challenging task in machine learning. In this paper, we develop a novel framework for detecting statistical interactions captured by a feedforward multilayer neural network by directly interpreting its learned weights. Depending on the desired interactions, our method can...
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Making intersections safer with I2V communication
Intersections are hazardous places. Threats arise from interactions among pedestrians, bicycles and vehicles, more complicated vehicle trajectories in the absence of lane markings, phases that prevent determining who has the right of way, invisible vehicle approaches, vehicle obstructions, and illegal movements. Thes...
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Convolutional Sparse Representations with Gradient Penalties
While convolutional sparse representations enjoy a number of useful properties, they have received limited attention for image reconstruction problems. The present paper compares the performance of block-based and convolutional sparse representations in the removal of Gaussian white noise. While the usual formulation...
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On the origin of the crescent-shaped distributions observed by MMS at the magnetopause
MMS observations recently confirmed that crescent-shaped electron velocity distributions in the plane perpendicular to the magnetic field occur in the electron diffusion region near reconnection sites at Earth's magnetopause. In this paper, we re-examine the origin of the crescent-shaped distributions in the light of...
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Projected support points: a new method for high-dimensional data reduction
In an era where big and high-dimensional data is readily available, data scientists are inevitably faced with the challenge of reducing this data for expensive downstream computation or analysis. To this end, we present here a new method for reducing high-dimensional big data into a representative point set, called p...
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AutonoVi: Autonomous Vehicle Planning with Dynamic Maneuvers and Traffic Constraints
We present AutonoVi:, a novel algorithm for autonomous vehicle navigation that supports dynamic maneuvers and satisfies traffic constraints and norms. Our approach is based on optimization-based maneuver planning that supports dynamic lane-changes, swerving, and braking in all traffic scenarios and guides the vehicle...
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On SGD's Failure in Practice: Characterizing and Overcoming Stalling
Stochastic Gradient Descent (SGD) is widely used in machine learning problems to efficiently perform empirical risk minimization, yet, in practice, SGD is known to stall before reaching the actual minimizer of the empirical risk. SGD stalling has often been attributed to its sensitivity to the conditioning of the pro...
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Composite Rational Functions and Arithmetic Progressions
In this paper we deal with composite rational functions having zeros and poles forming consecutive elements of an arithmetic progression. We also correct a result published earlier related to composite rational functions having a fixed number of zeros and poles.
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The Geometry of Concurrent Interaction: Handling Multiple Ports by Way of Multiple Tokens (Long Version)
We introduce a geometry of interaction model for Mazza's multiport interaction combinators, a graph-theoretic formalism which is able to faithfully capture concurrent computation as embodied by process algebras like the $\pi$-calculus. The introduced model is based on token machines in which not one but multiple toke...
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A High Space Density of Luminous Lyman Alpha Emitters at z~6.5
We present the results of a systematic search for Lyman-alpha emitters (LAEs) at $6 \lesssim z \lesssim 7.6$ using the HST WFC3 Infrared Spectroscopic Parallel (WISP) Survey. Our total volume over this redshift range is $\sim 8 \times10^5$ Mpc$^3$, comparable to many of the narrowband surveys despite their larger are...
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SYZ transforms for immersed Lagrangian multi-sections
In this paper, we study the geometry of the SYZ transform on a semi-flat Lagrangian torus fibration. Our starting point is an investigation on the relation between Lagrangian surgery of a pair of straight lines in a symplectic 2-torus and extension of holomorphic vector bundles over the mirror elliptic curve, via the...
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