On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

Trend · papers per month

count % of corpus

21 results for “PALM”

SG-PALM: a Fast Physically Interpretable Tensor Graphical Modelstat.ML

SG-PALM learns interpretable tensor models for high-dimensional data.

problem Learning interpretable tensor models for high-dimensional data.

method SG-PALM combines Sylvester generative model and fast proximal alternating linearized minimization.

result SG-PALM converges linearly to global optimum and scales to high dimensions.

tensor graphical models scalable inference physical interpretability sylvester model salamander

2021-05-26abs ↗pdf ↗

Planning with Abstract Learned Models While Learning Transferable Subtaskscs.LG

We introduce an algorithm for model-based hierarchical reinforcement learning to acquire self-contained transition and reward models suitable for probabilistic planning at multiple levels of abstraction. We call this framework Planning with Abstract Learned Models (PALM). By representing subtasks symbolically using a n…

2019-12-16abs ↗pdf ↗

Parallel Network Reconstruction with Multi-directional Regularizationmath.ST

PALMS reconstructs large-scale networks efficiently with parallel computing.

problem Reconstructing large-scale latent networks from observed dynamics is computationally challenging.

method PALMS (Parallel Adaptive Lasso with Multi-directional Signals) framework for distributed network reconstruction.

result PALMS substantially reduces computational complexity and storage requirements.

network reconstruction parallel computing compressed sensing adaptive regularization distributed optimization

2024-11-18abs ↗pdf ↗

Solving NMF with smoothness and sparsity constraints using PALMcs.LG

Non-negative matrix factorization is a problem of dimensionality reduction and source separation of data that has been widely used in many fields since it was studied in depth in 1999 by Lee and Seung, including in compression of data, document clustering, processing of audio spectrograms and astronomy. In this work we…

2019-10-31abs ↗pdf ↗

Heuristics for Efficient Sparse Blind Source Separationcs.LG

Sparse Blind Source Separation (sparse BSS) is a key method to analyze multichannel data in fields ranging from medical imaging to astrophysics. However, since it relies on seeking the solution of a non-convex penalized matrix factorization problem, its performances largely depend on the optimization strategy. In this …

2018-12-17abs ↗pdf ↗

Sparsity via Hyperpriors: A Theoretical and Algorithmic Study under Empirical Bayes Frameworkstat.ML

The paper studies sparsity in EBF with hyperpriors and proposes a PALM algorithm.

problem Promoting sparsity in sparse learning problems.

method Empirical Bayes framework, hyperpriors, proximal alternating linearized minimization (PALM) algorithm.

result Appropriate hyperpriors can significantly enhance sparsity and restoration accuracy.

sparsity empirical Bayes hyperpriors PALM image deblurring

2025-11-09abs ↗pdf ↗

An efficient algorithm for the

\ell_{p}

norm based metric nearness problemmath.OC

A new algorithm solves the metric nearness problem efficiently.

problem Finding the nearest distance matrix that satisfies triangle inequalities.

method Delayed constraint generation with semismooth Newton based proximal augmented Lagrangian method (PALM).

result Solves problems with up to 10^8 variables and 10^13 constraints efficiently.

metric nearness delayed constraint generation semismooth Newton proximal augmented Lagrangian method efficient algorithm

2022-11-02abs ↗pdf ↗

AudioPaLM: A Large Language Model That Can Speak and Listencs.CL

AudioPaLM combines text and speech models to improve speech processing and translation.

problem Improving speech understanding and generation models.

method Unified multimodal architecture combining text and speech models.

result AudioPaLM significantly outperforms existing speech translation systems.

large language model speech understanding speech generation speech translation multimodal architecture

2023-06-22abs ↗pdf ↗

Efficient algorithms for multivariate shape-constrained convex regression problemsmath.OC

Paper tackles multivariate shape-constrained convex regression problems.

problem Fitting a convex function to data with component-wise monotonicity and uniform Lipschitz continuity.

method Least squares estimator via solving a constrained convex quadratic programming problem. Efficient algorithms designed: sGS-ADMM and pALM.

result Both proposed algorithms outperform state-of-the-art methods in numerical experiments.

shape-constrained regression convex optimization quadratic programming alternating direction method proximal augmented Lagrangian

2020-02-26abs ↗pdf ↗

An Efficient Spatial Branch-and-Bound Algorithm for Global Optimization of Gaussian Process Posterior Mean Functionsmath.OC

A new algorithm optimizes Gaussian process posterior mean functions efficiently.

problem Optimizing Gaussian process posterior mean functions over hyperrectangles is challenging due to nonlinearity and nonconvexity.

method PALM-Mean, a piecewise-analytic lower-bounding framework embedded in reduced-space spatial branch-and-bound.

result PALM-Mean improves scalability for large datasets compared to general-purpose solvers.

Gaussian process global optimization branch-and-bound posterior mean piecewise-linear

2026-04-21abs ↗pdf ↗

Unsupervised Discretization by Two-dimensional MDL-based Histogramcs.LG

Proposes a new method for two-dimensional data discretization.

problem Discretization of multi-dimensional data, especially when dimensions are dependent.

method PALM algorithm, which alternately partitions and merges regions using the MDL principle.

result PALM accurately reveals ground truth partitions and approximates well outside the model class.

discretization two-dimensional MDL histogram multi-dimensional

2020-06-02abs ↗pdf ↗

Automatic lesion segmentation and Pathological Myopia classification in fundus imageseess.IV

The paper presents algorithms for diagnosing Pathological Myopia and detecting retinal structures.

problem Diagnosing Pathological Myopia and detecting retinal structures in fundus images.

method The approach uses Deep Learning techniques, including transfer learning with Xception and YOLO architecture.

result The method has shown satisfactory results in the Pathologic Myopia Challenge.

Deep Learning Pathological Myopia Retinal Structures Fundus Imaging Optic Disc

2020-02-15abs ↗pdf ↗

Estimation of sparse Gaussian graphical models with hidden clustering structuremath.OC

Proposes a method to estimate sparse Gaussian graphical models with hidden clustering structure.

problem Modeling statistical relationships between variables with sparsity and clustering.

method Two-phase algorithm using sGS-ADMM for initial point and pALM for solution.

result Demonstrates good performance and efficiency of the proposed model and algorithm on synthetic and real data.

Gaussian graphical models sparsity clustering concentration matrix two-phase algorithm

2020-04-17abs ↗pdf ↗

Convergence of the majorized PAM method with subspace correction for low-rank composite factorization modelmath.OC

Paper analyzes convergence of PAM method for low-rank factorization models.

problem Convergence analysis of PAM method with subspace correction for low-rank factorization models.

method Majorized proximal alternating minimization (PAM) method with subspace correction.

result Established full convergence of PAM method under KL property and column

\ell_{2,0}

-norm condition.

PAM method subspace correction low-rank factorization convergence analysis matrix completion

2024-06-07abs ↗pdf ↗

Time series forecasting from partial observations via Non-negative Matrix Factorizationcs.LG

Paper introduces SMM for forecasting multiple time series with missing values.

problem Forecasting multiple time series with missing and noisy values.

method Sliding Mask Method (SMM) using Non-negative Matrix Factorization (NMF).

result The method outperforms state-of-the-art methods in time series forecasting.

time series forecasting non-negative matrix factorization missing data proximal alternating linearized method

2021-02-10abs ↗pdf ↗

Galactica: A Large Language Model for Sciencecs.CL

Galactica learns from scientific literature to help researchers.

problem Information overload in scientific literature makes it hard to find useful insights.

method Trained on a large corpus of scientific papers, reference material, and knowledge bases.

result Outperforms existing models on various scientific tasks, including LaTeX equations and mathematical reasoning.

large language model scientific literature information overload search engines LaTeX

2022-11-16abs ↗pdf ↗

Multimodal Web Navigation with Instruction-Finetuned Foundation Modelscs.LG

WebGUM learns web navigation from multimodal data, outperforming previous methods.

problem Limited generalization from domain-specific models in web navigation.

method Instruction-following multimodal agent trained on vision-language foundation models.

result Significant improvement in web navigation performance on benchmarks.

web navigation multimodal learning foundation models instruction-following vision-language

2023-05-19abs ↗pdf ↗

Can ChatGPT Overcome Behavioral Biases in the Financial Sector? Classify-and-Rethink: Multi-Step Zero-Shot Reasoning in the Gold Investmentq-fin.ST

ChatGPT improves financial reasoning, overcoming biases in gold investment.

problem Improving financial reasoning and overcoming biases in investment decisions.

method Applied advanced prompt engineering and semantic news information to enhance LLMs' performance.

result ChatGPT with CoT prompt provides more explainable predictions and higher investment returns.

ChatGPT financial reasoning behavioral biases gold investment explainable predictions

2024-11-19abs ↗pdf ↗

Demixing Sparse Signals from Nonlinear Observations using Generalized Non-convex Regularizationstat.ML

New method recovers sparse signals from nonlinear observations with robust error bounds.

problem Recovering two sparse vectors from nonlinearly mixed observations with limited data.

method Regularization-based framework combining Huberized data fidelity and generalized folded-concave penalties with a proximal alternating algorithm.

result Estimation error bounds of order

σ\sqrt{s\log(n)/m}

at every localized stationary point, with oracle rate

σ\sqrt{s/m}

under beta-min condition.

sparse signals nonlinear observations regularization Huberized data fidelity proximal alternating algorithm

2026-07-12abs ↗pdf ↗

Generative Topological Networkscs.LG

Generative Topological Networks (GTNs) simplify latent space generation.

problem Complex latent space generation in generative models.

method GTNs use topology theory for a simple, supervised learning approach.

result GTNs improve upon VAEs and converge quickly, generating realistic samples.

Generative models Latent space Topology Topological networks Diffusion models

2024-06-21abs ↗pdf ↗

Sub-tree counts on hyperbolic random geometric graphsmath.PR

We study the hyperbolic random geometric graph introduced in Krioukov et al. For a sequence $R_n \to \infty$ , we define these graphs to have the vertex set as Poisson points distributed uniformly in balls $B(0,R_n) \subset B_d^α$ , the $d$ -dimensional Poincaré ball (unit d-ball with the Poincaré metric $d_α$ correspondi…

2018-02-16abs ↗pdf ↗