Quantum algorithm beats classical tools on complement sampling tasks

Quantum computers—devices that process information using quantum mechanical effects—have long been expected to outperform ...
IEEE

Adversarial Imitation Learning with General Function Approximation: Theoretical Analysis and Practical Algorithms

Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network approximation. However, existing ...
BGR

Squid Game's Unnecessary Final Season Is Another Example Of Algorithms Trumping Art

There's a familiar TV discourse taking shape online right now, the kind that I suspect will look awfully familiar to you if you remember the way Game of Thrones crashed and burned in its eighth and ...
GitHub

algorithm example not working on lyrat mini v1.2 (AUD-6461)

I (94) esp_image: segment 0: paddr=00010020 vaddr=3f400020 size=1e314h (123668) map I (133) esp_image: segment 1: paddr=0002e33c vaddr=3ff80000 size=0001ch ( 28) load I (133) esp_image: segment 2: ...
GitHub

Trust Region Preference Approximation: A simple and stable reinforcement learning algorithm for LLM reasoning

We propose the Trust Region Preference Approximation (TRPA) algorithm ⚙️, which integrates rule-based optimization with preference-based optimization for LLM reasoning tasks 🤖🧠. As a ...
IEEE

Approximation Algorithms for Noncommutative CSPs

Abstract: Noncommutative constraint satisfaction problems (CSPs) are higher-dimensional operator extensions of classical CSPs. Their approximability remains largely unexplored. A notable example of a ...
The Conversation

When AI plays favourites: How algorithmic bias shapes the hiring process

University of Calgary provides funding as a founding partner of The Conversation CA. University of Calgary provides funding as a member of The Conversation CA-FR. A public interest group filed a U.S.
Frontiers

Improving the convergence of an iterative algorithm for solving arbitrary linear equation systems using classical or quantum binary optimization

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution ...