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.

168,786 papers · 148 categories

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6 results for “novelty-seeking”

A Deep, Forgetful Novelty-Seeking Movie Recommender Modelcs.IR

A model predicts user movie preferences based on novelty-seeking traits.

problem Accurately predicting user movie preferences for competitive websites.

method DFNSM model uses demographic, genre, and novelty-seeking data.

result DFNSM outperforms previous models in movie recommendation accuracy.

novelty-seeking movie recommendation user behavior competitive websites deep learning

2019-09-02abs ↗pdf ↗

GRIMGEP: Learning Progress for Robust Goal Sampling in Visual Deep Reinforcement Learningcs.LG

Framework improves agent's ability to learn from noisy images.

problem Agents tend to focus on distracting regions in unsupervised image-based goal exploration.

method Proposes a novel framework combining absolute Learning Progress with unsupervised image-based goal exploration.

result Agents successfully identify and ignore distracting regions, improving overall performance.

Reinforcement Learning Goal Exploration Image-Based Absolute Learning Progress Novelty Seeking

2020-08-10abs ↗pdf ↗

Planning to Explore via Self-Supervised World Modelscs.LG

Plan2Explore learns new tasks efficiently through self-supervised planning.

problem Challenges in reinforcement learning, especially task-specific learning and sample efficiency.

method Self-supervised exploration and fast adaptation to new tasks through efficient planning.

result Plan2Explore outperforms prior methods in learning new tasks without supervision.

reinforcement learning self-supervised exploration planning task adaptation

2020-05-12abs ↗pdf ↗

Novel Policy Seeking with Constrained Optimizationcs.LG

Novel methods generate diverse policies in reinforcement learning.

problem Generating diverse policies in reinforcement learning.

method Constrained optimization perspective, introducing new metrics, and novel policy generation methods.

result Improved novelty and performance of generated policies.

reinforcement learning novel policies constrained optimization diversity cumulative reward

2020-05-21abs ↗pdf ↗

Expected Free Energy-based Planning as Variational Inferencestat.ML

Unified framework for planning under uncertainty using variational inference.

problem Planning under uncertainty with separate objectives for exploration and exploitation.

method Variational inference on a generative model augmented with priors.

result EFE-based planning emerges as variational inference, enabling scalable, resource-aware policies.

active inference variational inference free energy principle planning under uncertainty epistemic drives

2025-04-21abs ↗pdf ↗

Leveraging Skills from Unlabeled Prior Data for Efficient Online Explorationcs.LG

SUPE combines unlabeled data with RL to efficiently explore tasks.

problem Efficient exploration in reinforcement learning with sparse rewards.

method Extract low-level skills using VAE, pseudo-label unlabeled data, and use as off-policy data for online RL.

result SUPE outperforms prior methods across 42 long-horizon tasks.

reinforcement learning exploration unsupervised learning variational autoencoder online RL

2024-10-23abs ↗pdf ↗