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Arxiv:2109.04244V1 [Stat.Ml] 9 Sep 2024

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arXiv:2409.03495v1 [stat.ML] 5 Sep 2024 Maximum likelihood inference for high-dimensional problems ⋆ with multiaffine variable relations

arXiv:2305.11055v2 [stat.ML] 4 Sep 2024

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Current high-throughput technologies provide a large amount of variables to describe a phenomenon. Only a few variables are generally sufficient to answer the question.

The natural integration of extremely large antenna arrays (ELAAs) and terahertz (THz) communications can potentially achieve Tbps data rates in 6G networks. However, due Much of the literature on optimal design of bandit algorithms is based on minimization of expected regret. It is well known that designs that are optimal over certain

arXiv:2109.01433v1 [stat.ML] 3 Sep 2021 Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process In this paper, we have studied option pricing methods that are based on a Bayesian Markov-Switching Vector Autoregressive (MS-BVAR) process using a risk-neutral

1 Introduction NLP systems that operate in more than one lan-guage have been proven effective in tasks such as cross-lingual natural language understanding and machine translation (Devlin Abstract page for arXiv paper 2109.07582: Pareto-wise Ranking Classifier for Multi-objective Evolutionary Neural Architecture Search

arXiv:2109.05782v2 [cs.CL] 15 Sep 2024 Effectiveness of Pre-training for Few-shot Intent Classification

  • [2109.13595] The Fragility of Optimized Bandit Algorithms
  • arXiv:2109.00173v1 [stat.ML] 1 Sep 2021
  • arXiv:2409.03495v1 [stat.ML] 5 Sep 2024
  • [2109.03879] Emergence of robust memory manifolds

The ability to store continuous variables in the state of a biological system (e.g. a neural network) is critical for many behaviours. Most models for implementing such a memory ABSTRACT To infer a function value on a specific point x, it is essential to assign higher weights to the points closer to x, which is called local polynomial / multivariable regression. In many We use a generic formalism designed to search for relations in high-dimensional spaces to deter-mine if the total mass of a subhalo can be predicted from other internal properties such as

arXiv:2109.00173v1 [stat.ML] 1 Sep 2021 FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes

[2109.13246] Statistical strong lensing. III. Inferences with complete ...

arXiv:2406.09694v2 [stat.ML] 13 Sep 2024 An Eficient Approach to Regression Problems with Tensor Neural Networks* Abstract page for arXiv paper 2109.14764: Gaps, Ambiguity, and Establishing Complexity-Class Containments via Iterative Constant-Setting Sutton, Szepesvári and Maei introduced the first gradient temporal-difference (GTD) learning algorithms compatible with both linear function approximation and off-policy

In the deployment of deep neural models, how to effectively and automatically find feasible deep models under diverse design objectives is fundamental. Most existing neural is well known that designs Deep hashing approaches, including deep quantization and deep binary hashing, have become a common solution to large-scale image retrieval due to their high computation

Boyi Li2 Marco Pavone2 Abstract: Simulation stands as a cornerstone for safe and eficient autonomous driving development. At its core a simulation system ought to produce realis-tic, arXiv:2409.05381v1 [cs.CV] 9 Sep 2024 Boosting CLIP Adaptation for Image Quality Assessment via Meta-Prompt Learning and Gradient Regularization

J. Wu et al., “Recursively summarizing books with human feedback,” arXiv preprint arXiv:2109.10862, 2021. arXiv:2409.12691v1 [cs.CV] 19 Sep 2024 A dynamic vision sensor object recognition model based on trainable event-driven convolution and spiking attention mechanism

Abstract page for arXiv paper 2109.01051: Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? arXiv:2109.04014v1 [cs.CL] 9 Sep 2021 Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering Abstract Multi-party multi-turn dialogue comprehension brings un-precedented challenges on handling the complicated scenarios from multiple speakers and criss-crossed discourse

1 Introduction Many statistical procedures heavily rely on the assumptions made about the distribution of the empirical observations, and prove invalid if such conditions are Applications: Abstract page for arXiv Real-world situations where non-parametric extreme-bandits algorithms are naturally useful have been described in literature. For example, the randomized search situations

Abstract page for arXiv paper 2109.05729: CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation In this article we investigate the problem of computing Tamagawa numbers of CM tori. This problem arises naturally from the problem of counting polarized abelian varieties with Events such as the Financial Crisis of 2007-2008 or the COVID-19 pandemic caused significant losses to banks and insurance entities. They also demonstrated the

arXiv:2109.04335v1 [cs.CV] 9 Sep 2021 UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer

arXiv:2109.04242v1 [cs.CV] 9 Sep 2021 IICNet: A Generic Framework for Reversible Image Conversion

arXiv:2409.08311v1 [stat.ML] 12 Sep 2024 THEORETICAL GUARANTEES IN KL FOR DIFFUSION FLOW MATCHING MARTA GENTILONI SILVERI, GIOVANNI CONFORTI, AND