Tootfinder

Wealthfront, which uses AI to build investment portfolios, confidentially files for a US IPO; it was valued at $1.4B in 2022 during a failed acquisition by UBS (Prakhar Srivastava/Reuters)
https://www.reuters.com/technology/wealthf

ROBBO: An Efficient Method for Pareto Front Estimation with Guaranteed Accuracy
Roberto Boffadossi, Marco Leonesio, Lorenzo Fagiano
https://arxiv.org/abs/2506.18004

ROBBO: An Efficient Method for Pareto Front Estimation with Guaranteed Accuracy
A new method to estimate the Pareto Front (PF) in bi-objective optimization problems is presented. Assuming a continuous PF, the approach, named ROBBO (RObust and Balanced Bi-objective Optimization), needs to sample at most a finite, pre-computed number of PF points. Upon termination, it guarantees that the worst-case approximation error lies within a desired tolerance range, predefined by the decision maker, for each of the two objective functions. Theoretical results are derived, about the wo…

I agree with Luke Smith: we don’t actually need social media, the internet, or even computers to survive. Living below your means and simplifying your life is not only possible but straightforward if you choose to do it.
If you really care about Privacy, don't use the Internet!
https://peertube.wtf/w/wuw…

Effect Decomposition of Functional-Output Computer Experiments via Orthogonal Additive Gaussian Processes
Yu Tan, Yongxiang Li, Xiaowu Dai, Kwok-Leung Tsui
https://arxiv.org/abs/2506.12701

Effect Decomposition of Functional-Output Computer Experiments via Orthogonal Additive Gaussian Processes
Functional ANOVA (FANOVA) is a widely used variance-based sensitivity analysis tool. However, studies on functional-output FANOVA remain relatively scarce, especially for black-box computer experiments, which often involve complex and nonlinear functional-output relationships with unknown data distribution. Conventional approaches often rely on predefined basis functions or parametric structures that lack the flexibility to capture complex nonlinear relationships. Additionally, strong assumptio…

Miniaturized Chaos-assisted Spectrometer
Yujia Zhang, Chaojun Xu, Zhenyu Zhao, Yikai Su, Xuhan Guo
https://arxiv.org/abs/2506.15186 https://

Miniaturized Chaos-assisted Spectrometer
Computational spectrometers are at the forefront of spectroscopy, promising portable, on-chip, or in-situ spectrum analysis through the integration of advanced computational techniques into optical systems. However, existing computational spectrometer systems have yet to fully exploit optical properties due to imperfect spectral responses, resulting in increased system complexity and compromised performance in resolution, bandwidth, and footprint. In this study, we introduce optical chaos into …

Novel software for continuous wavelet analysis enable EEG real-time analysis on portable computers
Shoichiro Nakanishi
https://arxiv.org/abs/2506.07793 htt…

Novel software for continuous wavelet analysis enable EEG real-time analysis on portable computers
Continuous Wavelet Transform (CWT) is frequently used for waveform analysis. For example, in the field of neuroscience research, CWT is performed to analyze electroencephalograms (EEG) and calculate the index of brain activity. Recent advancements in computer technology, such as general-purpose computing on Graphics Processing Units (GPGPU), have enabled the application of CWT to real-time waveform analysis. However, the computational complexity of CWT is large, and it is challenging to employ …

Understanding the Error Sensitivity of Privacy-Aware Computing
Mat\'ias Mazzanti (University of Buenos Aires), Esteban Mocskos (University of Buenos Aires), Augusto Vega (IBM T. J. Watson Research Center), Pradip Bose (IBM T. J. Watson Research Center)
https://arxiv.org/abs/2506.07957

Understanding the Error Sensitivity of Privacy-Aware Computing
Homomorphic Encryption (HE) enables secure computation on encrypted data without decryption, allowing a great opportunity for privacy-preserving computation. In particular, domains such as healthcare, finance, and government, where data privacy and security are of utmost importance, can benefit from HE by enabling third-party computation and services on sensitive data. In other words, HE constitutes the "Holy Grail" of cryptography: data remains encrypted all the time, being protected while in …

Numerical approximation of a PDE-constrained Optimization problem that appears in Data-Driven Computational Mechanics
Pedro B. Bazon, Cristian G. Gebhardt, Gustavo C. Buscaglia, Roberto F. Ausas
https://arxiv.org/abs/2506.10894

Numerical approximation of a PDE-constrained Optimization problem that appears in Data-Driven Computational Mechanics
We investigate an optimization problem that arises when working within the paradigm of Data-Driven Computational Mechanics. In the context of the diffusion-reaction problem, such an optimization problem seeks for the continuous primal fields (gradient and flux) that are closest to some predefined discrete fields taken from a material data set. The optimization is performed over primal fields that satisfy the physical conservation law and the geometrical compatibility. We consider a reaction ter…

If you want to support the Fediverse financially, here's a way to do it: @…, a French non-profit, is raising money for the development of Peertube.
https://fediscience…

Software Portability for Computer Algebra
Arthur C. Norman, Stephen M. Watt
https://arxiv.org/abs/2506.01864 https://arxiv.org/pdf/25…

Software Portability for Computer Algebra
We have been involved in the creation of multiple software systems for computer algebra, including Reduce, Maple, Axiom and Aldor as well as a number of smaller specialised programs. We relate observations on how the meaning of software portability has changed over time and how it continues to evolve. We describe how the systems with which we have first-hand experience have achieved portability, how the central issues have changed over time and the challenges that remain.