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.

168,657 papers · 148 categories

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12 results for “self-loops”

Integral invariants for framed 3-manifolds associated to trivalent graphs possibly with self-loopsmath.GT

New theory defines invariants for framed 3-manifolds using trivalent graphs with self-loops.

problem Defining invariants for framed 3-manifolds with semi-simple Lie groups.

method Constructing graph complexes and cocycles, including self-loops, to define invariants.

result Higher-loop invariants can be defined by graph cocycles with or without self-loops.

3-manifolds integral invariants trivalent graphs self-loops Lie groups

2023-11-05abs ↗pdf ↗

Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphscs.LG

New algorithm reduces high-probability regret for time-varying feedback graphs.

problem High-probability regret bounds for adversarial bandits with time-varying feedback graphs.

method Online mirror descent framework with innovative techniques for pessimistic loss estimators.

result Achieves optimal high-probability regret bound for general and weakly observable graphs.

Adversarial bandits Time-varying feedback graphs High-probability regret Online mirror descent Pessimistic loss estimators

2022-10-04abs ↗pdf ↗

A Closer Look at Small-loss Bounds for Bandits with Graph Feedbackcs.LG

We study small-loss bounds for adversarial multi-armed bandits with graph feedback, that is, adaptive regret bounds that depend on the loss of the best arm or related quantities, instead of the total number of rounds. We derive the first small-loss bound for general strongly observable graphs, resolving an open problem…

2020-02-02abs ↗pdf ↗

Characterizing the memory capacity of transmon qubit reservoirsq-fin.RM

Study characterizes memory capacity of quantum reservoirs using transmon qubits.

problem Understanding the memory capacity of quantum reservoirs built with transmon qubits.

method Characterized memory capacity of quantum reservoirs using transmon qubits from IBM, focusing on NMSE and topology complexity.

result Found a peak in memory capacity for configurations with n-1 self-loops, suggesting optimal design for forecasting tasks.

quantum reservoir computing transmon qubits memory capacity NMSE topology complexity

2020-04-15abs ↗pdf ↗

Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processescs.LG

The paper develops CI tests for causal discovery in SDEs.

problem Inferring causal structure from stochastic dynamical systems.

method Developed CI constraints and a CI test for SDEs.

result Proposed CI test outperforms existing methods.

causal discovery stochastic differential equations conditional independence signature kernel CI test

2024-02-28abs ↗pdf ↗

EEGNN: Edge Enhanced Graph Neural Network with a Bayesian Nonparametric Graph Modelstat.ML

EEGNN improves graph neural networks by enhancing graph structure.

problem Mis-simplification of graphs by removing self-loops and unweighted edges reduces GNN performance.

method Proposes EEGNN framework using DMPGM for better graph structural information.

result EEGNN achieves significant performance improvement over baselines.

graph neural networks mis-simplification Bayesian nonparametric Markov chain Monte Carlo structural information

2022-08-12abs ↗pdf ↗

Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classificationcs.LG

Unified model combines feature and label propagation for semi-supervised classification.

problem Combining feature and label propagation for effective semi-supervised classification.

method Unified Message Passing Model (UniMP) using Graph Transformer and masked label prediction.

result Obtains new state-of-the-art results in Open Graph Benchmark (OGB).

Graph Neural Network Label Propagation Semi-Supervised Classification Unified Model Masked Label Prediction

2020-09-08abs ↗pdf ↗

Reconstructing undirected graphs from eigenspacesmath.ST

In this paper, we aim at recovering an undirected weighted graph of $N$ vertices from the knowledge of a perturbed version of the eigenspaces of its adjacency matrix $W$ . For instance, this situation arises for stationary signals on graphs or for Markov chains observed at random times. Our approach is based on minimizi…

2016-03-26abs ↗pdf ↗

Doubly-Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noisestat.ML

Doubly-stochastic normalization improves robustness to heteroskedastic noise.

problem Robustness to heteroskedastic noise in affinity matrix construction.

method Doubly-stochastic normalization of the Gaussian kernel.

result Doubly-stochastic normalization converges to clean matrix with rate

m^{-1/2}

under heteroskedastic noise.

kernel methods affinity matrix doubly-stochastic normalization heteroskedastic noise robustness

2020-05-31abs ↗pdf ↗

Adversarial Combinatorial Semi-bandits with Graph Feedbackcs.LG

This paper extends combinatorial semi-bandits to graph feedback, improving regret bounds.

problem Adversarial combinatorial semi-bandits with graph feedback.

method Introduced graph feedback in combinatorial semi-bandits, using convexified actions and online stochastic mirror descent.

result Optimal regret scales as

S\sqrt{T}+\sqrt{αST}

, interpolating between full and semi-bandit feedback.

combinatorial semi-bandits graph feedback regret analysis convexified actions online mirror descent

2025-02-26abs ↗pdf ↗

Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networkscs.LG

Study optimal spectral estimator for semi-supervised node classification.

problem Semi-supervised node classification on CSBM with limited labels.

method Spectral estimator inspired by PCA, graph ridge regression, GCN.

result Achieves information-theoretical threshold for exact recovery.

Semi-supervised learning Spectral methods Graph Convolutional Networks Contextual Stochastic Block Model Principal Component Analysis

2024-12-18abs ↗pdf ↗

International trade has been increasingly organized in the form of global value chains (GVCs) where different stages of production are located in different countries. This recent phenomenon has substantial consequences for both trade policy design at the national or regional level and business decision making at the fi…

2015-08-18abs ↗pdf ↗