Adversarial configurations improve SPL classifier and implementation.
problem Predicting product acceptability in SPLs is impractical.
method Adversarial Machine Learning to create new configurations.
result Improves classifier and SPL engineering.
On-device research index
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.
169,181 papers · 148 categories
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48 results for “Software Product Line”
Python tool assesses European agricultural production resilience.
problem Estimating resilience of European agricultural production systems.
method Python software to compute annual production resilience indicator.
result Demonstrates resilience of European agricultural production.
Models of complex systems are often formalized as sequential software simulators: computationally intensive programs that iteratively build up probable system configurations given parameters and initial conditions. These simulators enable modelers to capture effects that are difficult to characterize analytically or su…
Paper proposes a new Markov model for efficient PLC system design.
problem Efficient estimation of Markov model parameters for bursty error channels.
method Introduced a Block Diagonal Markov model and a modified Baum-Welch algorithm.
result Efficient estimation of state transition matrix for PLC system design.
Quantifying Process Quality: The Role of Effective Organizational Learning in Software Evolutioncs.SE
Improving software quality through effective organizational learning.
problem Lack of reliable quantification methods for software evolution.
method Leveraging application lifecycle management data to identify and address managerial practices.
result Effective learning from past processes improves software quality indirectly.
DRIFT uses RL to automate functional software testing efficiently.
problem Efficient and reliable automated software testing.
method DRIFT employs Q-learning with Graph Neural Networks on symbolic UI representations.
result DRIFT can robustly test software functionalities in a fully automated manner.
SySeVR uses deep learning to detect software vulnerabilities.
problem Detecting software vulnerabilities is challenging and important.
method SySeVR combines syntax and semantic information to represent programs for deep learning.
result SySeVR detects 15 unknown vulnerabilities, including 7 unknown and 8 silently patched ones.
This paper discusses challenges in integrating ML in software companies.
problem Challenges in integrating Machine Learning in software companies.
method Discussion of challenges faced by Atlassian.
result The importance of human involvement in ML systems.
Among eight possible geometric structures on three-dimensional manifolds less studied from the differential geometric point of view are those modelled on the Heisenberg group . We consider the Heisenberg left-invariant metric and use some results on Levi-Civita connection and curvature tensor to present solutio…
This paper tackles co-design of neural hardware and software to improve efficiency.
problem Designing efficient deep learning systems that consider both hardware and software optimizations together.
method Developed a constrained Bayesian optimization framework to automatically identify profitable design points in the joint hardware/software design space.
result Improved energy-delay product by 18% (ResNet) and 40% (DQN) over hand-tuned systems.
LineFlow is a framework for training RL agents to control production lines.
problem Designing control systems for production lines is challenging.
method Introduces LineFlow, an extensible Python framework for simulating and training RL agents.
result RL agents approach optimal performance in well-understood scenarios but face challenges in complex industrial lines.
Dynamic constructions of hyperbolisms of plane curves: an automated exploration of geometric locimath.AG
Automatically explores geometric loci of curves using software networking.
problem Exploring hyperbolisms and geometric loci of plane curves.
method Parametric equations, Groebner bases, and elimination for deriving polynomial equations.
result Derives new constructions of lemniscates and other geometric loci.
We use a control framework to analyze the digital vendor's profit maximization problem. The vendor captures market share by focusing costly effort on post-launch product maintenance, which influences user perception of the product and drives a revenue stream associated with product use. Our theoretical results show nec…
This study compares traditional ML and deep learning for classifying multilingual user feedback.
problem Classifying multilingual user feedback for software development teams.
method Comparison of traditional machine learning and deep learning approaches.
result Traditional machine learning can achieve comparable results to deep learning for multilingual user feedback classification.
EvaSylv software evaluates forest management with natural risk considerations.
problem Evaluating forest management under increased natural risk due to climate change.
method User-friendly software simulates forest management scenarios, integrating natural risk using a Poisson process and Faustmann approach.
result Software optimizes forest management criteria like Faustmann value and Averaged yield value.
Painlevé analysis identifies integrable cases of Ricci solitons over specific warped products and line bundles.
problem Finding integrable cases of Ricci solitons over warped products and line bundles.
method Painlevé analysis applied to cohomogeneity one steady Ricci soliton equations for two classes of solitons: warped products and complex line bundles over a Fano Kähler Einstein base.
result Integrable cases identified for specific dimensions and configurations of Ricci solitons.
Framework for AI healthcare products from concept to market.
problem Failure of AI products to reach clinics despite promising potential.
method Decision-making framework for AI healthcare product development.
result Guides through a three-phase process to market launch of validated AI products.
Study the monodromy and center-focus problems for rational maps defined by products of generic lines.
problem Monodromy and center-focus problems for rational maps defined by products of generic lines.
method Analyze the 1-homology group and meromorphic 1-forms to characterize vanishing Abelian integrals.
result Characterize meromorphic 1-forms whose Abelian integrals vanish on cycles around a center singularity.
Transfer learning improves performance modeling by reducing model construction cost.
problem Reducing the cost of constructing performance models for configurable systems.
method Empirical study on four software systems, varying configurations and environmental conditions.
result Transfer learning is beneficial for small environmental changes but only reduces sampling efficiency for severe changes.
In this short article I introduce the knotR package, which creates two dimensional knot diagrams optimized for visual appearance using the R programming language. The knotR package is a systematic R-centric suite of software for the creation of production-quality artwork of knot diagrams, released under GPL2.
Only products of projective lines have vanishing Futaki invariants for all Kähler classes.
problem Finding Bott manifolds with vanishing Futaki invariants for all Kähler classes.
method Proving isomorphism to products of projective lines.
result Only products of projective lines satisfy the condition.
We give local, explicit representation formulas for n-dimensional spacelike submanifolds which are marginally trapped in the Minkowski space, the de Sitter and anti de Sitter spaces and the Lorentzian products of the sphere and the hyperbolic space by the real line.
Using Premia and Nsp for Constructing a Risk Management Benchmark for Testing Parallel Architecturecs.CE
Financial institutions have massive computations to carry out overnight which are very demanding in terms of the consumed CPU. The challenge is to price many different products on a cluster-like architecture. We have used the Premia software to valuate the financial derivatives. In this work, we explain how Premia can …
The Alesker-Poincare pairing for smooth valuations on manifolds is expressed in terms of the Rumin differential operator acting on the cosphere-bundle. It is shown that the derivation operator, the signature operator and the Laplace operator acting on smooth valuations are formally self-adjoint with respect to this pai…
TreeCaps improves code comprehension for software developers.
problem Processing code efficiently for software developers.
method Tree-based capsule networks for capturing code syntactical structures and dependencies.
result TreeCaps outperforms other approaches in classifying program functionalities.
This paper is a more succinct version of the author's 1993 UCLA mathematics thesis. It proves that any group quasi-isometric to the product of the hyperbolic plane with the real line is a finite extension of a cocompact lattice in either the isometry group of the product of the hyperbolic plane with the real line or th…
Metric spaces uniquely split into Hilbert and non-line-split parts.
problem Understanding the structure of metric spaces.
method Proved unique decomposition into Hilbert and non-line-split parts.
result Metric spaces have a unique decomposition into a Hilbert space and a non-line-split part.
OS-ELM outperforms other classifiers in software defect prediction.
problem Predicting software defects from imbalanced datasets.
method OS-ELM, oversampling with noise filtering, comparison with other classifiers.
result OS-ELM outperforms other classifiers in recall and balanced accuracy.
Explores security challenges of machine learning in real-world systems.
problem Vulnerabilities in machine learning models deployed in safety-critical systems.
method Broadens systems security view of ML vulnerabilities, identifies novel challenges, proposes mitigation suggestions.
result Highlights novel challenges and proposes mitigation strategies for securing ML systems.
Software and hardware co-design and optimization of HPC systems has become intolerably complex, ad-hoc, time consuming and error prone due to enormous number of available design and optimization choices, complex interactions between all software and hardware components, and multiple strict requirements placed on perfor…
Paper presents machine learning approach for detecting software vulnerabilities.
problem Detect subtle security vulnerabilities in production software.
method Data-driven approach using machine learning on C and C++ code.
result Highest performing model achieves AUC of 0.87 on ROC curve.
Dr.S recommends cancer drugs based on genomic data.
problem Personalizing cancer treatments using genomic information.
method Machine learning to identify optimal drug-gene associations.
result Developed a Drug Recommendation System (Dr.S) for cancer cell lines.
The notion of a local line bundle on a manifold, classified by 2-cohomology with real coefficients, is introduced. The twisting of pseudodifferential operators by such a line bundle leads to an algebroid with elliptic elements with real-valued index, given by a twisted variant of the Atiyah-Singer index formula. Using …
In this note we present a characterization of those open n-manifolds (n>4), whose products with the real line are homeomorphic to interiors of compact (n+1)-manifolds with boundary.
A MARL system improves productivity on a metallurgical pickling line.
problem Improving productivity on a metallurgical pickling line.
method Combines mathematical modeling and Multi-Agent Reinforcement Learning (MARL).
result Significant improvement in automation systems.
We study the distribution of the common zero sets of -tuples of holomorphic sections of powers of singular Hermitian pseudo-effective line bundles on a compact Kähler manifold. As an application, we obtain sufficient conditions which ensure that the wedge product of the curvature currents of these line bundles c…
Estimates curvature for long-time continuity method solutions.
problem Curvature estimates for long-time continuity method solutions.
method Adapting arguments from Kähler-Ricci flow to semi-ample canonical line bundles.
result Derives curvature bounds for product manifolds.
Study of monodromy and vanishing cycles for complete intersection curves.
problem Computing topological monodromy of complete intersection curves.
method Innovative tools for studying monodromy of tensor products of very ample line bundles, induction on multi-degree.
result Answer given by the r-spin mapping class group associated to the maximal root of the adjoint line bundle.
Our aim is to generalize the result that two generic complex line arrangements are equivalent. In fact for a line arrangement A we associate its defining polynomial, the product of a_ix+b_iy+c_i, so that A = (f=0). We prove that the defining polynomials of two generic line arrangements are, up to a small deformation, t…
MISIM improves code similarity systems with neural learning.
problem Improving accuracy of code semantics similarity systems.
method Context-aware semantics structure and neural code similarity scoring algorithm.
result MISIM achieves 8.08% better accuracy than state-of-the-art systems.
Adaptive RL optimizes testing resource allocation for dynamic software environments.
problem Optimizing resource allocation for evolving software testing environments.
method Integrates Q-learning with hybrid reward design for sequential decision-making.
result Consistently outperforms static and optimization-based baselines in simulation studies.
In this paper, we investigate the condition on warped product manifold of a Kenmotsu manifold and the real line to be a conformal Kahler manifold. This result demonstrates the close relation of Kenmotsu and Kahler manifolds.
Deployable probabilistic programming for Go and other languages.
problem Adding probabilistic programming to mainstream languages.
method Design guidelines and Infergo implementation for Go.
result Infergo demonstrates performance and applicability in various use cases.
Study stability of operators on warped product manifolds.
problem Stability of operators on warped product manifolds.
method Examined the family of operators in a warped product of an infinite interval or real line by a compact manifold.
result Stability of the operators was studied in a specific type of manifold.
In this note, we answer affirmatively the question if a warped product of a compact manifold with a line as an ancient solution to the Ricci flow is trivial. We also consider the global behavior of the Type III warping product Ricci flow.
Proposes using entity embedding vectors to improve Gaussian Process models for knowledge transfer across cell lines.
problem Lack of reuse of experimental data for predicting novel processes.
method Hybrid Gaussian Process models with entity embedding vectors to represent product identity.
result Improved performance in predicting novel processes compared to traditional methods.
CK simplifies ML model deployment and reproducibility with open APIs and DevOps.
problem Making ML models reproducible and deployable across different environments.
method Decompose complex systems into reusable sub-components with unified APIs and DevOps principles.
result Automatically co-design and optimize ML models for speed, accuracy, energy, and size.
The symmetric product of vector fields on a manifold arises when one studies the controllability of certain classes of mechanical control systems. A geometric description of the symmetric product is provided using parallel transport, along the lines of the flow interpretation of the Lie bracket. This geometric interpre…