Copertina

Exploring approaches to computational representation and classification of user-generated meal logs

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Hu, Guanlan, Anand, Adit, Desai, Pooja M., Urteaga, Iñigo, Mamykina, Lena
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference
di: Ketenci, Mert, et al.
Pubblicazione: (2023)

Next-generation reservoir computing validated by classification task
di: Kitayama, Ken-ichi
Pubblicazione: (2025)

Association between nutritional factors, inflammatory biomarkers and cancer types: an analysis of NHANES data using machine learning
di: Liu, Yuqing, et al.
Pubblicazione: (2025)

Anomaly detection in time-series via inductive biases in the latent space of conditional normalizing flows
di: Baumgartner, David, et al.
Pubblicazione: (2026)

Probabilistic Shapley Value Modeling and Inference
di: Ketenci, Mert, et al.
Pubblicazione: (2024)

Canonical Bayesian Linear System Identification
di: Bryutkin, Andrey, et al.
Pubblicazione: (2025)

Sequential Monte Carlo Bandits
di: Urteaga, Iñigo, et al.
Pubblicazione: (2018)

Structured Reinforcement Learning for Incentivized Stochastic Covert Optimization
di: Jain, Adit, et al.
Pubblicazione: (2024)

Classifier Language Models: Unifying Sparse Finetuning and Adaptive Tokenization for Specialized Classification Tasks
di: Krishnan, Adit, et al.
Pubblicazione: (2025)

A hierarchy tree data structure for behavior-based user segment representation
di: Liu, Yang, et al.
Pubblicazione: (2025)

Learning to Reason with Mixture of Tokens
di: Jain, Adit, et al.
Pubblicazione: (2025)

Exploring polymer classification with a hybrid single-photon quantum approach
di: Stoyanova, Alexandrina, et al.
Pubblicazione: (2025)

On the Identifiability of Tensor Ranks via Prior Predictive Matching
di: da Silva, Eliezer, et al.
Pubblicazione: (2025)

CEV-LM: Controlled Edit Vector Language Model for Shaping Natural Language Generations
di: Moorjani, Samraj, et al.
Pubblicazione: (2024)

Optimal and computationally tractable lower bounds for logistic log-likelihoods
di: Anceschi, Niccolò, et al.
Pubblicazione: (2024)

An Intelligent Robotic and Bio-Digestor Framework for Smart Waste Management
di: Khatri, Radhika, et al.
Pubblicazione: (2026)

Directional Concentration Uncertainty: A representational approach to uncertainty quantification for generative models
di: Chattopadhyay, Souradeep, et al.
Pubblicazione: (2026)

Towards Greener Nights: Exploring AI-Driven Solutions for Light Pollution Management
di: Varshney, Paras, et al.
Pubblicazione: (2024)

ML-based approach to classification and generation of structured light propagation in turbulent media
di: Wang, Aokun, et al.
Pubblicazione: (2026)

Understanding Interpretability by generalized distillation in Supervised Classification
di: Agarwal, Adit, et al.
Pubblicazione: (2020)

Exploring Equity of Climate Policies using Multi-Agent Multi-Objective Reinforcement Learning
di: Biswas, Palok, et al.
Pubblicazione: (2025)

Interacting Large Language Model Agents. Interpretable Models and Social Learning
di: Jain, Adit, et al.
Pubblicazione: (2024)

Well log data generation and imputation using sequence-based generative adversarial networks
di: Al-Fakih, Abdulrahman, et al.
Pubblicazione: (2024)

Investigation into using stochastic embedding representations for evaluating the trustworthiness of the Fréchet Inception Distance
di: Bench, Ciaran, et al.
Pubblicazione: (2026)

AKReF: An argumentative knowledge representation framework for structured argumentation
di: Bhattacharjee, Debarati, et al.
Pubblicazione: (2025)

Time series classification with random convolution kernels: pooling operators and input representations matter
di: Lo, Mouhamadou Mansour, et al.
Pubblicazione: (2024)

Exploring the limits of Hierarchical World Models in Reinforcement Learning
di: Schiewer, Robin, et al.
Pubblicazione: (2024)

Exploring the Promise and Limits of Real-Time Recurrent Learning
di: Irie, Kazuki, et al.
Pubblicazione: (2023)

Self-Aligned Reward: Towards Effective and Efficient Reasoners
di: Han, Peixuan, et al.
Pubblicazione: (2025)

Adaptive kernel-density approach for imbalanced binary classification
di: Nishimura, Kotaro J., et al.
Pubblicazione: (2025)

Density Operator Expectation Maximization
di: Vishnu, Adit, et al.
Pubblicazione: (2025)

Disentangling representations of retinal images with generative models
di: Müller, Sarah, et al.
Pubblicazione: (2024)

Unified Bayesian representation for high-dimensional multi-modal biomedical data for small-sample classification
di: Belenguer-Llorens, Albert, et al.
Pubblicazione: (2024)

Multimodal graph representation learning for website generation based on visual sketch
di: Vu, Tung D., et al.
Pubblicazione: (2025)

A rank decomposition for the topological classification of neural representations
di: Beshkov, Kosio, et al.
Pubblicazione: (2024)

Mechanical in-sensor computing: a programmable meta-sensor for structural damage classification without external electronic power
di: Zhang, Tingpeng, et al.
Pubblicazione: (2025)

Granular-ball computing: an efficient, robust, and interpretable adaptive multi-granularity representation and computation method
di: Xia, Shuyin, et al.
Pubblicazione: (2023)

Tensor-based computation of the Koopman generator via operator logarithm
di: Kishimoto, Tatsuya, et al.
Pubblicazione: (2026)

Automobile demand forecasting: Spatiotemporal and hierarchical modeling, life cycle dynamics, and user-generated online information
di: Nahrendorf, Tom, et al.
Pubblicazione: (2025)

Synthetic medical data generation: state of the art and application to trauma mechanism classification
di: Doremus, Océane, et al.
Pubblicazione: (2025)