arXiv:2604.00811v1 Announce Type: new Abstract: Overlap, also known as positivity, is a key condition for causal treatment effect estimation. Many popular estimators suffer from high variance and become brittle when features differ strongly across treatment groups. This is especially challenging in high dimensions: the curse of dimensionality can make overlap implausible. To address this, we propose a class of feature representations called deconfounding scores, which preserve both identification and the target of estimation; the classical propensity and prognostic […]

Ver mais

The code needed configuration values. AI GENERATED # config.pyDATABASE_URL = “postgresql://localhost/mydb”API_KEY = “sk_live_abc123″DEBUG = True# app.pyimport configdef connect_database(): return psycopg2.connect(config.DATABASE_URL)def call_api(endpoint): return requests.get(f”https://api.example.com/{endpoint}”, headers={‘X-API-Key’: config.API_KEY}) Clean. Simple. Every module could access configuration through import config. No passing parameters everywhere. Convenient. Then the bug reports started. “The app works fine on my machine but not in production.” “Tests pass locally but fail in CI.” “Feature works when run alone but breaks when run after other tests.” I couldn’t reproduce any of […]

Ver mais

arXiv:2504.15243v2 Announce Type: replace-cross Abstract: Constrained optimization with multiple functional inequality constraints has significant applications in machine learning. This paper examines a crucial subset of such problems where both the objective and constraint functions are weakly convex. Existing methods often face limitations, including slow convergence rates or reliance on double-loop algorithmic designs. To overcome these challenges, we introduce a novel single-loop penalty-based stochastic algorithm. Following the classical exact penalty method, our approach employs a {bf hinge-based penalty}, which […]

Ver mais

arXiv:2601.19963v1 Announce Type: new Abstract: Cross-session nonstationarity in neural activity recorded by implanted electrodes is a major challenge for invasive Brain-computer interfaces (BCIs), as decoders trained on data from one session often fail to generalize to subsequent sessions. This issue is further exacerbated in practice, as retraining or adapting decoders becomes particularly challenging when only limited data are available from a new session. To address this challenge, we propose a Task-Conditioned Latent Alignment framework (TCLA) for cross-session neural […]

Ver mais

South by Southwest 2026 hosts a remarkable concentration of awards ceremonies across audio, film, television, and digital culture. This guide covers the three major podcasting award events in detail: the 2026 iHeartPodcast Awards, the inaugural Independent Podcast and Creator Awards (Indie PaC Awards), the SXSW Film & TV Awards, each distinct in format, eligibility, and what they recognize. The SXSW Awards Schedule Fri–Sat, March 13–14: SXSW Pitch : Startup showcase across nine categories, a live audience and a […]

Ver mais

arXiv:2405.06479v4 Announce Type: replace-cross Abstract: Weighted conformal prediction (WCP) has been commonly used to quantify prediction uncertainty under covariate shift. However, the effectiveness of WCP relies heavily on the degree of overlap between the training and test covariate distributions. This challenge is exacerbated in multi-source settings with varying covariate distributions, where direct application of WCP can be impractical. In this paper, we address the multi-source setup by leveraging WCP under the assumption of a shared conditional distribution. We […]

Ver mais

arXiv:2601.08065v1 Announce Type: new Abstract: Forward reachability analysis is the predominant approach for verifying reach-avoid properties in neural feedback systems (dynamical systems controlled by neural networks). This dominance stems from the limited scalability of existing backward reachability methods. In this work, we introduce new algorithms that compute both over- and under-approximations of backward reachable sets for such systems. We further integrate these backward algorithms with established forward analysis techniques to yield a unified verification framework for neural feedback […]

Ver mais