Tootfinder

Boosting Accelerated Proximal Gradient Method with Adaptive Sampling for Stochastic Composite Optimization
Dongxuan Zhu, Weihuan Huang, Caihua Chen
https://arxiv.org/abs/2507.18277

Boosting Accelerated Proximal Gradient Method with Adaptive Sampling for Stochastic Composite Optimization
We develop an adaptive Nesterov accelerated proximal gradient (adaNAPG) algorithm for stochastic composite optimization problems, boosting the Nesterov accelerated proximal gradient (NAPG) algorithm through the integration of an adaptive sampling strategy for gradient estimation. We provide a complexity analysis demonstrating that the new algorithm, adaNAPG, achieves both the optimal iteration complexity and the optimal sample complexity as outlined in the existing literature. Additionally, we …

Quantum-Enhanced Optimization by Warm Starts
Ieva \v{C}epait\.e, Niam Vaishnav, Leo Zhou, Ashley Montanaro
https://arxiv.org/abs/2508.16309 https://arxiv.o…

Quantum-Enhanced Optimization by Warm Starts
We present an approach, which we term quantum-enhanced optimization, to accelerate classical optimization algorithms by leveraging quantum sampling. Our method uses quantum-generated samples as warm starts to classical heuristics for solving challenging combinatorial problems like Max-Cut and Maximum Independent Set (MIS). To implement the method efficiently, we introduce novel parameter-setting strategies for the Quantum Approximate Optimization Algorithm (QAOA), qubit mapping and routing tech…

Finding congruences with the WZ method
Li-Quan Feng, Qing-Hu Hou
https://arxiv.org/abs/2506.19221 https://arxiv.org/pdf/2506.19221

Finding congruences with the WZ method
We utilize the Wilf-Zeilberger (WZ) method to establish congruences related to truncated Ramanujan-type series. By constructing hypergeometric terms $f(k, a, b, \ldots)$ with Gosper-summable differences and selecting appropriate parameters, we derive several congruences modulo $p$ and $p^2$ for primes $p > 2$. For instance, we prove that for any prime $p > 2$, \[ \sum_{n=0}^{p-1} \frac{10n+3}{2^{3n}}\binom{3n}{n}\binom{2n}{n}^2 \equiv 0 \pmod{p},\] and \[ \sum_{n=0}^{p-1} \frac{(-1)^n(20n^2+8n+…

The surprising strength of weak classifiers for validating neural posterior estimates
Vansh Bansal, Tianyu Chen, James G. Scott
https://arxiv.org/abs/2507.17026

The surprising strength of weak classifiers for validating neural posterior estimates
Neural Posterior Estimation (NPE) has emerged as a powerful approach for amortized Bayesian inference when the true posterior $p(θ\mid y)$ is intractable or difficult to sample. But evaluating the accuracy of neural posterior estimates remains challenging, with existing methods suffering from major limitations. One appealing and widely used method is the classifier two-sample test (C2ST), where a classifier is trained to distinguish samples from the true posterior $p(θ\mid y)$ versus the lear…

Code Generation for Near-Roofline Finite Element Actions on GPUs from Symbolic Variational Forms
Kaushik Kulkarni, Andreas Kl\"ockner
https://arxiv.org/abs/2506.17471

Code Generation for Near-Roofline Finite Element Actions on GPUs from Symbolic Variational Forms
We present a novel parallelization strategy for evaluating Finite Element Method (FEM) variational forms on GPUs, focusing on those that are expressible through the Unified Form Language (UFL) on simplex meshes. We base our approach on code transformations, wherein we construct a space of scheduling candidates and rank them via a heuristic cost model to effectively handle the large diversity of computational workloads that can be expressed in this way. We present a design of a search space to w…

@… regarding your Java 25 CPU profiling work. Both in your articles as well as the JEP509 the current sub-sampling method doesn't mention Safepoints? Is that not a thing anymore for current profiling? I was always under the impression that except for async-profiler all other profiler needs threads to be in safepoints? Thx (Writing another German art…

Estimating the growth rate of a birth and death process using data from a small sample
Carola Sophia Heinzel, Jason Schweinsberg
https://arxiv.org/abs/2508.16110 https://…

Estimating the growth rate of a birth and death process using data from a small sample
The problem of estimating the growth rate of a birth and death processes based on the coalescence times of a sample of $n$ individuals has been considered by several authors (\cite{stadler2009incomplete, williams2022life, mitchell2022clonal, Johnson2023}). This problem has applications, for example, to cancer research, when one is interested in determining the growth rate of a clone. Recently, \cite{Johnson2023} proposed an analytical method for estimating the growth rate using the theory of …

A Novel Monte-Carlo Compressed Sensing and Dictionary Learning Method for the Efficient Path Planning of Remote Sensing Robots
Alghalya Al-Hajri, Ejmen Al-Ubejdij, Aiman Erbad, Ali Safa
https://arxiv.org/abs/2507.18462

A Novel Monte-Carlo Compressed Sensing and Dictionary Learning Method for the Efficient Path Planning of Remote Sensing Robots
In recent years, Compressed Sensing (CS) has gained significant interest as a technique for acquiring high-resolution sensory data using fewer measurements than traditional Nyquist sampling requires. At the same time, autonomous robotic platforms such as drones and rovers have become increasingly popular tools for remote sensing and environmental monitoring tasks, including measurements of temperature, humidity, and air quality. Within this context, this paper presents, to the best of our knowl…

Closed-Form Decomposition for Simplicial Cones and PDBarv Algorithm for Lattice Point Counting
Sihao Tao, Guoce Xin, Zihao Zhang
https://arxiv.org/abs/2506.19322

Closed-Form Decomposition for Simplicial Cones and PDBarv Algorithm for Lattice Point Counting
Counting lattice points within a rational polytope is a foundational problem with applications across mathematics and computer science. A key approach is Barvinok's algorithm, which decomposes the lattice point generating function of cones to that of unimodular cones. However, standard implementations face difficulties: the original primal method struggles with points on cone boundaries, while the alternative dual method can be slow for certain cone types. This paper introduces two main contr…

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…