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This https://arxiv.org/abs/2503.13965 has been replaced.
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First-Order Projected Algorithms With the Same Linear Convergence Rate Bounds as Their Unconstrained Counterparts
In this paper, we propose a systematic approach for constructing first-order projected algorithms for optimization problems with general set constraints, building upon their unconstrained counterparts. We show that these projected algorithms retain the same linear convergence rate bounds, when the latter are obtained for the unconstrained algorithms via quadratic Lyapunov functions arising from integral quadratic constraint (IQC) characterizations. The projected algorithms are constructed by ap…

Improving AI-generated music with user-guided training
Vishwa Mohan Singh, Sai Anirudh Aryasomayajula, Ahan Chatterjee, Beste Aydemir, Rifat Mehreen Amin
https://arxiv.org/abs/2506.04852

Improving AI-generated music with user-guided training
AI music generation has advanced rapidly, with models like diffusion and autoregressive algorithms enabling high-fidelity outputs. These tools can alter styles, mix instruments, or isolate them. Since sound can be visualized as spectrograms, image-generation algorithms can be applied to generate novel music. However, these algorithms are typically trained on fixed datasets, which makes it challenging for them to interpret and respond to user input accurately. This is especially problematic beca…

D-Rex: Heterogeneity-Aware Reliability Framework and Adaptive Algorithms for Distributed Storage
Maxime Gonthier (University of Chicago, Argonne National Laboratory), Dante D. Sanchez-Gallegos (Universidad Carlos III de Madrid), Haochen Pan (University of Chicago), Bogdan Nicolae (Argonne National Laboratory), Sicheng Zhou (Southern University of Science and Technology), Hai Duc Nguyen (University of Chicago, Argonne National Laboratory), Valerie Hayot-Sasson (University of Chicago, Ar…

D-Rex: Heterogeneity-Aware Reliability Framework and Adaptive Algorithms for Distributed Storage
The exponential growth of data necessitates distributed storage models, such as peer-to-peer systems and data federations. While distributed storage can reduce costs and increase reliability, the heterogeneity in storage capacity, I/O performance, and failure rates of storage resources makes their efficient use a challenge. Further, node failures are common and can lead to data unavailability and even data loss. Erasure coding is a common resiliency strategy implemented in storage systems to mi…

Computing matrix $\varphi$-functions arising in exponential integrators
Awad H. Al-Mohy, Xiaobo Liu
https://arxiv.org/abs/2506.01193 https://

Computing matrix $φ$-functions arising in exponential integrators
A new scaling and recovering algorithm is proposed for simultaneously computing the matrix $φ$-functions that arise in exponential integrator methods for the numerical solution of certain first-order systems of ordinary differential equations (ODEs). The algorithm initially scales the input matrix down by a nonnegative integer power of two, then computes the $[m/m]$ diagonal Padé approximant to $φ_p$, where $p$ is the largest index of interest. The remaining $[m+p{-}j/m]$ Padé approximants …

Solving Euclidean Problems by Isotropic Initialization
Khusrav Yorov, Bolun Wang, Mikhail Skopenkov, Helmut Pottmann, Caigui Jiang
https://arxiv.org/abs/2506.01726

Solving Euclidean Problems by Isotropic Initialization
Many problems in Euclidean geometry, arising in computational design and fabrication, amount to a system of constraints, which is challenging to solve. We suggest a new general approach to the solution, which is to start with analogous problems in isotropic geometry. Isotropic geometry can be viewed as a structure-preserving simplification of Euclidean geometry. The solutions found in the isotropic case give insight and can initialize optimization algorithms to solve the original Euclidean prob…