Landlords could no longer rely on rent-pricing software to quietly track each other's moves and push rents higher using confidential data, under a settlement between RealPage Inc. and federal ...

Posts from this topic will be added to your daily email digest and your homepage feed. A new bill would hold social media platforms responsible for foreseeable algorithmic harms. A new bill would hold ...

Note: The CUDA version requires significant GPU memory for large problems. For a 64x64 gridworld (4096 states), approximately 1GB of GPU memory is needed. If you encounter "out of memory" errors, try ...

To the Portland City Council, the core issue with the proposed rent-algorithm ban is whether it will deter developers from building new housing. (TNS) — The Portland City Council will vote as soon as ...

BRUSSELS, Nov 4 (Reuters) - Meta Platforms (META.O), opens new tab on Tuesday rejected a ruling by the French rights watchdog against its algorithm after allegations of discriminatory job ...

Compliance, compute and cross-border rules are becoming the true arbiters of A.I. advantage. Unsplash+ The contest for A.I. leadership has shifted from lab breakthroughs to law books. Over the next ...

Abstract: In this paper, we introduce a method called Multiplayer Cascaded Policy Iteration (MCPI) for finding Nash equilibrium solutions to non-zero-sum (NZS) differential games. While policy ...

Rasner Media CEO Reid Rasner on Thursday announced that he would no longer seek a bid to purchase the controversial social media app TikTok, citing concerns about national security in regards to China ...

NEW YORK, July 9 (Reuters) - TikTok is preparing to launch a standalone app for U.S. users that is expected to operate on a separate algorithm and data system from its global app, laying the ...

Abstract: Two-player zero-sum games often rely on solving the game algebraic Riccati equation (GARE) in the linear case. However, existing approaches for solving the GARE typically require stringent ...

We propose Q-Policy, a hybrid quantum-classical reinforcement learning (RL) framework that mathematically accelerates policy evaluation and optimization by exploiting quantum computing primitives.