Results 41 to 50 of about 16,277 (238)

Online Learning in Kernelized Markov Decision Processes

CoRR, 2018
22nd International Conference on Artificial Intelligence and Statistics (AISTATS ...
Sayak Ray Chowdhury, Aditya Gopalan
openaire   +4 more sources

STRIDE: A Sequencing Depth Robust Metric for Sparse Chromosome Conformation Capture Data Comparison

Advanced Science, EarlyView.
A mean first passage time (MFPT)‐based representation transforms sparse Hi‐C contact maps into robust topological representations, preserving biologically meaningful chromatin features and facilitating robust analysis of TADs, chromatin loops, differential chromatin contacts, and sparse single‐cell Hi‐C data.
Bingxiang Xu, Xiaomeng Gao, Weichu Tao, Zhihua Zhang, Feifei Li   +4 more
wiley   +1 more source

A Kernel Perspective on Behavioural Metrics for Markov Decision Processes

CoRR, 2023
Behavioural metrics have been shown to be an effective mechanism for constructing representations in reinforcement learning. We present a novel perspective on behavioural metrics for Markov decision processes via the use of positive definite kernels.
Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland 0001   +3 more
openaire   +3 more sources

ReLink: Reliable Deep Learning for Microscopic Motion Tracking

Advanced Science, EarlyView.
ReLink enables reliable trajectory linking in single‐particle tracking by integrating physics‐informed motion statistics with confidence‐based adaptive filtering. Across diverse simulated and experimental conditions, ReLink robustly reconstructs trajectories and preserves the fidelity of downstream analyses, enabling accurate characterization of ...
Yuan Jiang, Xiaochen Feng, Hongda Wei, Hao Sha, Hongpeng Wang, Min Zhang, Sanyang Han, Yongbing Zhang   +7 more
wiley   +1 more source

Integration of Multivariate Beta-based Hidden Markov Models and Support Vector Machines with Medical Applications

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022
In this paper, we propose a novel hybrid discriminative generative model by integrating a modified version of hidden Markov model (HMM), multivariate Beta-based HMM with support vector machine (SVM). We apply Fisher Kernel to define decision boundary and
Narges Manouchehri, Nizar Bouguila
doaj   +1 more source

Value of Information of Improved Traceability in Fresh Produce Markets

Agribusiness, EarlyView.
ABSTRACT Traceability plays an important role in promoting a safe food supply by fostering transparent information exchange along the food supply chain. New technological innovations have the potential to improve traceability outcomes, as greater transparency along the food supply chain can aid in pinpointing precise origins of the contamination ...
Kelsey Vourazeris, Mark R. Manfredo, Michael N. Kozicki   +2 more
wiley   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Positive Operator Valued Measures and Feller Markov kernels [PDF]

Journal of Mathematical Analysis and Applications, 2016
A Positive Operator Valued Measure (POVM) is a map $F:\mathcal{B}(X)\to\mathcal{L}_s^+(\mathcal{H})$ from the Borel $σ$-algebra of a topological space $X$ to the space of positive self-adjoint operators on a Hilbert space $\mathcal{H}$. We assume $X$ to be Hausdorff, locally compact and second countable and prove that a POVM $F$ is commutative if and ...
openaire   +3 more sources

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Hybrid Markov weighted fuzzy kernel time series with red Piranha Walrus optimization for gold price forecasting

Ain Shams Engineering Journal
The price of gold is crucial to the world’s financial and economic systems; hence precise estimation of gold prices is essential. The current study proposes a hybrid Markov Weighted Fuzzy Kernel Time Series framework for gold price prediction, together ...
Gijy S. Pillai, M. Immaculate Mary
doaj   +1 more source