Tootfinder

Control and optimization for Neural Partial Differential Equations in Supervised Learning
Alain Bensoussan, Minh-Binh Tran, Bangjie Wang
https://arxiv.org/abs/2506.20764

Control and optimization for Neural Partial Differential Equations in Supervised Learning
Although there is a substantial body of literature on control and optimization problems for parabolic and hyperbolic systems, the specific problem of controlling and optimizing the coefficients of the associated operators within such systems has not yet been thoroughly explored. In this work, we aim to initiate a line of research in control theory focused on optimizing and controlling the coefficients of these operators-a problem that naturally arises in the context of neural networks and super…

Belgian startup nox.energy, one 🚀 to watch in the smart energy space, has launched its new tool to optimize heat pumps: smart control based on weather forecast, to increase solar self-consumption, for (static/dynamic) tariff optimization and additional flexibility trading as independent aggregator
https://app.nox.energy

Reinforcement Learning for Optimal Control of Spin Magnetometers
Logan W. Cooke, Stefanie Czischek
https://arxiv.org/abs/2506.21475 https://

Reinforcement Learning for Optimal Control of Spin Magnetometers
Quantum optimal control in the presence of decoherence is difficult, particularly when not all Hamiltonian parameters are known precisely, as in quantum sensing applications. In this context, maximizing the sensitivity of the system is the objective, for which the optimal target state or unitary transformations are unknown, especially in the case of multi-parameter estimation. Here, we investigate the use of reinforcement learning (RL), specifically the soft actor-critic (SAC) algorithm, for pr…

Efficient Optimization Accelerator Framework for Multistate Ising Problems
Chirag Garg, Sayeef Salahuddin
https://arxiv.org/abs/2505.20250 https://

Efficient Optimization Accelerator Framework for Multistate Ising Problems
Ising Machines are a prominent class of hardware architectures that aim to solve NP-hard combinatorial optimization problems. These machines consist of a network of interacting binary spins/neurons that evolve to represent the optimum ground state energy solution. Generally, combinatorial problems are transformed into quadratic unconstrained binary optimization (QUBO) form to harness the computational efficiency of these Ising machines. However, this transformation, especially for multi-state p…

iPhone-Diebe nutzen Spear-Phishing, um Entsperr-PIN abzugreifen
Geklaute iPhones sind oftmals gut gesichert. Diebe wollen unbedingt an die Geräte-PIN. Dafür nutzen sie zunehmend professionellere Tricks.

Audience Optimization - 4 Ways to Increase Streaming Royalties
#MusicianTips #UnsignedMusician

Audience Optimization - 4 Ways to Increase Streaming Royalties
Stan Stewart - @muz4now

G$^{2}$D: Boosting Multimodal Learning with Gradient-Guided Distillation
Mohammed Rakib, Arunkumar Bagavathi
https://arxiv.org/abs/2506.21514 https://

G$^{2}$D: Boosting Multimodal Learning with Gradient-Guided Distillation
Multimodal learning aims to leverage information from diverse data modalities to achieve more comprehensive performance. However, conventional multimodal models often suffer from modality imbalance, where one or a few modalities dominate model optimization, leading to suboptimal feature representation and underutilization of weak modalities. To address this challenge, we introduce Gradient-Guided Distillation (G$^{2}$D), a knowledge distillation framework that optimizes the multimodal model wit…

Religion, PLpol
It's about time I elaborated on an earlier thought.
"Non-practicing Catholics" have more liberal worldview than "conservative" Catholics — and often they jeer at them. These qualities make it easy to forget that you're draining with Catholics. But when the push comes to shove, you discover that you can't rely on them. They won't openly oppose the Church, they won't protect the people who are "immoral" according to Catholic morality, and if they are forced to choose a side, they'll side with the Catholics.
The Polish PO/KO party (often perceived as "liberal") is just like that. Their views are more liberal than the conservative right wing, they love portraying themselves as an opposition to it, but in the end they are a right-wing party. When it's convenient to them, they happily present liberal postulates — but they are as fast to withdraw them to please their right-wing electorate.
#PLpol

Block Coordinate Descent Network Simplex for Optimal Transport
Lingrui Li, Nobuo Yamashita
https://arxiv.org/abs/2506.21231 https://a…

Block Coordinate Descent Network Simplex for Optimal Transport
We propose the Block Coordinate Descent Network Simplex (BCDNS) method for solving large-scale discrete Optimal Transport (OT) problems. BCDNS integrates the Network Simplex (NS) algorithm with a block coordinate descent (BCD) strategy, decomposing the full problem into smaller subproblems per iteration and reusing basis variables to ensure feasibility. We prove that BCDNS terminates in a finite number of iterations with an exact optimal solution, and we characterize its per-iteration complexit…

OptGM: An Optimized Gate Merging Method to Mitigate NBTI in Digital Circuits
Maryam Ghane, Amir M. Hajisadeghi, Hamid R. Zarandi
https://arxiv.org/abs/2506.21487

OptGM: An Optimized Gate Merging Method to Mitigate NBTI in Digital Circuits
This paper presents OptGM, an optimized gate merging method designed to mitigate negative bias temperature instability (NBTI) in digital circuits. First, the proposed approach effectively identifies NBTI-critical internal nodes, defined as those with a signal probability exceeding a predefined threshold. Next, based on the proposed optimized algorithm, the sensitizer gate (which drives the critical node) and the sensitive gate (which is fed by it) are merged into a new complex gate. This comple…