Deep neural networks are notorious for being sensitive to small well-chosen perturbations, and estimating the regularity of such architectures is of utmost importance for safe and robust practical applications. In this paper, we investigate one of the key characteristics to assess the regularity of such methods: the Lipschitz constant of deep learning architectures.

Samsung Galaxy Unpacked 2026 is Feb. 25 Valve's Steam Machine: Everything we know Some users are mourning GPT-4o's discontinuation on February 13, despite the concerns that the cult-favorite model was dangerously sycophantic. OpenAI's GPT-4o may have survived its first brush with going offline, but it won't be as lucky this time. OpenAI has officially retired GPT-4o, the ChatGPT model that was seen as more conversational and notoriously sycophantic, on February 13. The news of GPT-4o's end was first announced in a post on the OpenAI website in January, but the discontinuation also included GPT-5, GPT-4.1, However, a wave of user complaints led OpenAI to restore access to GPT-4o but with no guarantee that it'll be around forever.

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NeurIPS 2019 Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center "2626" "Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning" The reviewers unanimously support acceptance. We encourage the authors to strongly consider the suggestions provided by the reviewers for improving a camera ready version.

We thank all the reviewers for their encouraging comments. In both these cases, τ is effectively zero. Liu et al. shows how GTD-class algorithms can be formally derived using a primal-dual saddle point Sutton et al. presents a (single time-scale) variant of linear TD learning, which they call emphatic TD and show that They also provide an asymptotic convergence analysis to the set of local optima. If the paper is accepted, we will work further on improving the clarity of the work.

One emerging area of research is the fast adaptation of large text-to-image models to smaller datasets or new visual concepts.

Inadditiontothememory limitation, there are other important concerns.