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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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82163245326 · Jun 202019922001200920172026
48 results for ICT systems

Method uses Seq2Seq learning to automatically generate recovery commands for ICT systems.

problem Manual decision-making for recovery commands is time-consuming and error-prone.
method Seq2Seq neural network model trained on past logs and commands.
result The model can estimate accurate recovery commands from new failures.

Dividing deep learning models for consistent anomaly detection in changing log data.

problem Anomaly detection methods fail when log data types change, leading to false negatives.
method Divide deep learning models based on log data correlation and extract correlations.
result Continues anomaly detection accuracy even when log data changes.

We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi-supervised learning paradigm. ICT encourages the prediction at an interpolation of unlabeled points to be consistent with the interpolation of the predictions at those points…

2019-03-09abs ↗pdf ↗

Estimates individual treatment effects using gradient interpolation and kernel smoothing.

problem Estimating individualized continuous treatment effects in observational data.
method Augment training data with independently sampled treatments and inferred counterfactual outcomes using gradient interpolation and kernel smoothing.
result Our method outperforms state-of-the-art methods on counterfactual estimation error.

Study on electronic banking satisfaction in Nigeria.

problem Limited research on factors enhancing end users' satisfaction in electronic banking.
method Empirical analysis of factors influencing electronic banking user satisfaction.
result Factors influencing electronic banking user satisfaction and their relationship with satisfaction.

Our society has been computerised and globalised due to emergence and spread of information and communication technology (ICT). This enables us to investigate our own socio-economic systems based on large amounts of data on human activities. In this article, methods of treating complexity arising from a vast amount of …

2012-10-17abs ↗pdf ↗

The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which are foreseen to revolutionize our world {via} creating new services and applications in a variety of sectors such as environmental monitoring, mobile-health systems, intelligent transportation systems and so on. The {information and …

2018-10-29abs ↗pdf ↗

New study shows min-max algorithms can converge to non-stationary points.

problem Challenges in min-max optimization due to periodic cycles and spurious attractors.
method Analyzed state-of-the-art algorithms and heuristics in non-convex/non-concave problems.
result Spurious attractors can prevent min-max algorithms from reaching true optima.

In recent years, the interest in Big Data sources has been steadily growing within the Official Statistic community. The Italian National Institute of Statistics (Istat) is currently carrying out several Big Data pilot studies. One of these studies, the ICT Big Data pilot, aims at exploiting massive amounts of textual …

2019-10-22abs ↗pdf ↗

Recent introduction of ICT in agriculture has brought a number of changes in the way farming is done. This means use of Internet of Things(IoT), Cloud Computing(CC), Big Data (BD) and automation to gain better control over the process of farming. As the use of these technologies in farms has grown exponentially with ma…

2019-07-15abs ↗pdf ↗

How technology affects growth or employment has long been debated. With a hiatus, the debate revived once again in the form of how Information and Communications Technology, as a form of new technology, exerts on productivity and employment. Information and Communications Technology perceived as General Purpose Technol…

2017-04-05abs ↗pdf ↗

TACE unifies scalar and tensorial modeling in Cartesian space for accurate, stable, and efficient atomistic predictions.

problem Complexity and challenges in equivariant atomistic machine learning models.
method Tensor Atomic Cluster Expansion (TACE) in Cartesian space, decomposing local environments into irreducible Cartesian tensors (ICT).
result Universal invariant and equivariant embeddings, enabling explicit control at inference.

This work develops secure distributed algorithms for machine learning to protect against data poisoning and network attacks.

problem Vulnerability of distributed machine learning algorithms to cyber threats.
method Game-theoretic framework to capture conflicting goals of a learner and an attacker, iterative distributed algorithm.
result Distributed SVM is prone to fail in different types of attacks, with impact depending on network structure and attack capabilities.

Orchestrating the Twin Transition in GBS: A Socio-Technical Framework

problem MNCs' need to harmonize digital efficiency with environmental stewardship
method Technology Roadmapping (TRM) with ICT-centric innovation ecosystem toolkit
result Central 'operational airlock' for GBS in harmonizing digital and environmental transformation

We consider the large-scale query-document retrieval problem: given a query (e.g., a question), return the set of relevant documents (e.g., paragraphs containing the answer) from a large document corpus. This problem is often solved in two steps. The retrieval phase first reduces the solution space, returning a subset …

2020-02-10abs ↗pdf ↗

Overview of integrable systems with symmetries, focusing on toric and semitoric systems.

problem Classifying and understanding integrable systems with symmetries.
method Using decorated polygons and controlled bifurcations in one-parameter families of systems.
result Construction of explicit semitoric systems with prescribed invariants.

Learning to control linear systems is statistically hard, especially for underactuated systems.

problem Statistical difficulty of learning to control linear systems, especially underactuated ones.
method Utilized minimax lower bounds and structural assumptions to prove learning complexity can be exponential.
result Learning complexity can be at most exponential with the controllability index of the system.

Discrete-time systems can be characterized by simple flat coordinates and their shifts.

problem Characterizing flatness of discrete-time systems.
method Developed a map from flat coordinates and their shifts to system state and input, fulfilling system equations identically.
result Derived necessary conditions for a system to be flat, without requiring differential geometry methods.

The paper explores when linear system identification is hard or easy, especially for under-actuated systems.

problem Statistical hardness of learning linear systems, especially under-actuated or under-excited systems.
method Using tools from minimax theory and recent statistical tools for finite sample analysis of system identification.
result The controllability index of linear systems affects the sample complexity of identification, making some systems hard to learn.

This paper improves system identification by reducing sample complexity for high-dimensional linear dynamical systems.

problem High sample complexity for learning partially observed linear dynamical systems in high dimensions.
method Introduces an 1\ell_1-regularized estimation method that reduces sample complexity from linear to logarithmic with system dimension.
result Markov parameters can be learned with logarithmic number of samples relative to system dimension, improving sample complexity.

In integrable hydrodynamic systems, coordinates exist where generators and symmetries are simple.

problem Existence of Riemannian invariants for integrable systems of hydrodynamic type.
method Finding coordinates where the generator and all symmetries are diagonal.
result In integrable hydrodynamic systems, there exist coordinates where the generator and all symmetries are diagonal.

This paper studies nonholonomic constraints in Hamiltonian systems, deriving equations and theorems.

problem Analyzing nonholonomic constraints in Hamiltonian systems.
method Deriving distributional RCH systems, geometric constraint conditions, and Hamilton-Jacobi theorems.
result Derives precise geometric constraint conditions and Hamilton-Jacobi theorems for nonholonomic systems.

This paper considers control systems defined on Lie algebroids. After deriving basic controllability tests for general control systems, we specialize our discussion to the class of mechanical control systems on Lie algebroids. This class of systems includes mechanical systems subject to holonomic and nonholonomic const…

2004-02-26abs ↗pdf ↗

Systemic risk refers to the risk that the financial system is susceptible to failures due to the characteristics of the system itself. The tremendous cost of systemic risk requires the design and implementation of tools for the efficient macroprudential regulation of financial institutions. The current paper proposes a…

2015-02-27abs ↗pdf ↗

The paper develops methods to derive mixed superposition rules for Lie systems and applies them to various physical systems.

problem Finding general solutions for Lie systems.
method Develops mixed superposition rules for Lie systems with imprimitive Lie algebras and semidirect sums.
result Extends coalgebra method to Lie systems of partial differential equations.

Paper develops reduction theory for controlled Lagrangian systems with symmetry and momentum map.

problem Reduction of controlled Lagrangian systems with symmetry and momentum map.
method Using Legendre transformation and Euler-Lagrange vector field, the paper extends symmetric reduction theory.
result Established regular reduction theory for RCL systems with symmetry and momentum map.

The paper studies connections in superintegrable systems, revealing geometric insights.

problem Understanding non- and semi-degenerate superintegrable systems.
method Analyzes two torsion-free connections associated with superintegrable systems.
result Semi-degenerate secondary structure tensor is the Ricci curvature of a natural torsion-free connection.

This paper proposes a system-agnostic policy for dynamic scheduling.

problem Dynamic scheduling in changing systems is challenging due to system-specific optimal policies.
method Descriptive policy that learns a system-agnostic scheduling principle.
result System-agnostic meta-learning enables adaptation to unseen system characteristics.

New Lie systems derived from Goursat distributions with applications to differential equations.

problem Analyzing Lie systems associated with Goursat distributions and their applications.
method Analyzing bracket-generating distributions and their relation to Lie systems, focusing on reductions and reconstructions.
result Lie systems associated with Goursat distributions can be reduced and solutions reconstructed from reduced systems.