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.

169,051 papers · 148 categories

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6 results for “path-tracking”

Learning and Generalizing Motion Primitives from Driving Data for Path-Tracking Applicationscs.LG

This paper learns motion primitives from driving data to improve vehicle path-tracking.

problem Improving vehicle path-tracking accuracy through learned motion primitives.

method Two-level structure with path segmentation and clustering; Gaussian Mixture Model (GMM) and Gaussian Mixture Regression (GMR).

result The model predicts future lateral control commands with high accuracy.

motion primitives path-tracking Gaussian Mixture Model Gaussian Mixture Regression intelligent vehicles

2018-06-02abs ↗pdf ↗

Statistical Pattern Recognition for Driving Styles Based on Bayesian Probability and Kernel Density Estimationstat.ML

Driving styles have a great influence on vehicle fuel economy, active safety, and drivability. To recognize driving styles of path-tracking behaviors for different divers, a statistical pattern-recognition method is developed to deal with the uncertainty of driving styles or characteristics based on probability density…

2016-06-03abs ↗pdf ↗

Driving Decision and Control for Autonomous Lane Change based on Deep Reinforcement Learningcs.RO

The paper uses deep reinforcement learning to control autonomous lane changes safely.

problem Safe and efficient autonomous lane changes in vehicles.

method Deep Q-networks and quadratic approximators for decision-making and control.

result Demonstrated effectiveness in simulations for decision-making and control.

autonomous driving lane change deep reinforcement learning safety control

2019-04-23abs ↗pdf ↗

Nonparametric Extrema Analysis in Time Series for Envelope Extraction, Peak Detection and Clusteringcs.LG

A nonparametric method for time series analysis extracts envelopes, detects peaks, and clusters data.

problem Extracting envelopes, detecting peaks, and clustering in time series data.

method Iterative procedure that minimizes

L_1

drift to create upper and lower bounding signals, using Viterbi-like path tracking and optimal elimination rules.

result Efficiently calculated solution with near-linear time complexities for various applications.

time series nonparametric envelope extraction peak detection clustering

2021-09-05abs ↗pdf ↗

Provably Robust Blackbox Optimization for Reinforcement Learningcs.LG

New algorithm RBO improves RL in noisy environments.

problem Derivative-free optimization sensitivity to noisy rewards and dynamics.

method Robust Blackbox Optimization (RBO) using gradient flows and robust regression.

result RBO can recover gradients to high accuracy even with up to 23% corrupted measurements.

Reinforcement Learning Gradient Optimization Robust Regression Noisy Rewards Evolutionary Strategies

2019-03-07abs ↗pdf ↗

Causal-driven attribution (CDA): Estimating channel influence without user-level datastat.ML

CDA framework infers channel influence from aggregated data without user identifiers.

problem Lack of user-level path data due to privacy regulations and platform restrictions.

method CDA integrates PCMCI for causal discovery and Structural Causal Model for effect estimation.

result CDA achieves strong accuracy in estimating channel influence, even under structural uncertainty.

Attribution modelling Marketing effectiveness Causal discovery Privacy-preserving Temporal causal

2025-12-24abs ↗pdf ↗