Tootfinder

Optimization for Semantic-Aware Resource Allocation under CPT-based Utilities
Symeon Vaidanis, Photios A. Stavrou, Marios Kountouris
https://arxiv.org/abs/2506.04952

Optimization for Semantic-Aware Resource Allocation under CPT-based Utilities
The problem of resource allocation in goal-oriented semantic communication with semantic-aware utilities and subjective risk perception is studied here. By linking information importance to risk aversion, we model agent behavior using Cumulative Prospect Theory (CPT), which incorporates risk-sensitive utility functions and nonlinear transformations of distributions, reflecting subjective perceptions of gains and losses. The objective is to maximize the aggregate utility across multiple CPT-mode…

US political contradictions; knowledge systems
As Trump at least partially succeeds in constructing an alternate reality for his most ardent followers, it's tempting to think of his dogma as false, in contrast to some imagined "truth" which his non-followers are smart enough to believe in. But a more nuanced view of knowledge would admit that different groups of people have different shared truths, constituting different knowledge systems which each deviate from what's objectively measurable in different ways, and in fact they each accept different standards of what is objective, so there's not really a single "ground truth" we can even compare to to determine which of these knowledge systems is "more correct" (similar problems arise even if we only care about "more useful").
To make this more concrete, we can see that e.g., competing quantum physics theories, or likewise competing religious beliefs, have no reasonable basis on which to judge between them, either in terms of "truth" or "utility." So the Trump-dogma knowledge system, although bad, morally repugnant, etc., can't so easily be dismissed as "false" in my view. "Distorted" or "malignant" or "evil" or "contradictory" are better monikers, in my opinion.
But what I'm even more interested in thinking about is: in what ways does the current American liberal "common sense" knowledge system already bear the scars of past fascist lies & contradictions? I can think of a few:
"Columbus was an explorer."
This is "factually accurate" in the same way some of Trump's propaganda is, but it's also a cruel distortion of "Columbus was a child murderer," and it's a misrepresentation that serves an evil purpose, yet which is widely taught in elementary schools today.
Another: "dropping atomic bombs on civilians in Japan was necessary to end WWII."
Perhaps in the future we'll have "family separation & the 2025 ICE crackdowns were necessary to end the immigration crisis," although I dearly hope not.
"Reparations for slavery aren't reasonable," is yet another...
I'll close this rambling with a question: what other fascist lies have you noticed that are normalized in America right now from past Trump-like leaders (or even from less overtly fascist institutions)?

Migrated two utility VMs to LXC containers. It's cool and all, and pretty neat that I can literally dump the filesystem from the VM and start it almost unmodified as a container, but udev rules don't work inside LXC so I'm kinda shafted with one of them. 50% is still a passing grade these days, right?

House budget bill would kill 330K solar, storage jobs: SEIA | Utility Dive
https://www.utilitydive.com/news/solar-storage-jobs-house-budget-trump/749617/

SMOTE-DP: Improving Privacy-Utility Tradeoff with Synthetic Data
Yan Zhou, Bradley Malin, Murat Kantarcioglu
https://arxiv.org/abs/2506.01907 https://

SMOTE-DP: Improving Privacy-Utility Tradeoff with Synthetic Data
Privacy-preserving data publication, including synthetic data sharing, often experiences trade-offs between privacy and utility. Synthetic data is generally more effective than data anonymization in balancing this trade-off, however, not without its own challenges. Synthetic data produced by generative models trained on source data may inadvertently reveal information about outliers. Techniques specifically designed for preserving privacy, such as introducing noise to satisfy differential priva…

"We honestly should rename GIMP: It's a bad name. | think a new and better acronym would substantially improve brand recognition.
Free Utility for Creative Kits, Brushes, Overlays, & Imaging:
FUCKBOI"
https://lemmy.ca/comment/16863046

GIMP - Lemmy.ca

FERC skimps on winter storm details as staffing cuts threaten future reporting | Utility Dive
https://www.utilitydive.com/news/ferc-winter-storm-report-staffing-cuts-ucs/749586/

This https://arxiv.org/abs/2312.11797 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Data-Driven Merton's Strategies via Policy Randomization
We study Merton's expected utility maximization problem in an incomplete market, characterized by a factor process in addition to the stock price process, where all the model primitives are unknown. The agent under consideration is a price taker who has access only to the stock and factor value processes and the instantaneous volatility. We propose an auxiliary problem in which the agent can invoke policy randomization according to a specific class of Gaussian distributions, and prove that the …

Proportional Response Dynamics in Gross Substitutes Markets
Yun Kuen Cheung, Richard Cole, Yixin Tao
https://arxiv.org/abs/2506.02852 https://

Proportional Response Dynamics in Gross Substitutes Markets
Proportional response is a well-established distributed algorithm which has been shown to converge to competitive equilibria in both Fisher and Arrow-Debreu markets, for various sub-families of homogeneous utilities, including linear and constant elasticity of substitution utilities. We propose a natural generalization of proportional response for gross substitutes utilities, and prove that it converges to competitive equilibria in Fisher markets. This is the first convergence result of a propo…

This https://arxiv.org/abs/2505.23436 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Emergent Risk Awareness in Rational Agents under Resource Constraints
Advanced reasoning models with agentic capabilities (AI agents) are deployed to interact with humans and to solve sequential decision-making problems under (approximate) utility functions and internal models. When such problems have resource or failure constraints where action sequences may be forcibly terminated once resources are exhausted, agents face implicit trade-offs that reshape their utility-driven (rational) behaviour. Additionally, since these agents are typically commissioned by a h…