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#online-learning

Downside-Controlled Online Forecast Combination under Delayed and Revised Outcomes

arXiv cs.LG ↗ · 4d ago Cached

This paper proposes a method for improving frozen forecasters by combining static and online correctors to control downside risk, demonstrating gains up to 11.5% in benchmarks and reduced errors in electricity load forecasting.

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#online-learning

Beyond Class Marginals: Bounding Rehearsal Gaps without Freezing Class Co-occurrence

arXiv cs.LG ↗ · 6d ago Cached

This paper introduces randomized-pass replay (RPR) to bound rehearsal gaps in online continual learning, showing improved accuracy over independent class-balanced retrieval in experience replay methods like ER-ACE.

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#online-learning

Lightweight Ranking Heads: Accelerating Multi-Task Experimentation in Production Recommender Systems

arXiv cs.LG ↗ · 6d ago Cached

This paper introduces the Lightweight Ranking Heads framework to accelerate multi-task experimentation in production recommender systems by enabling dynamic task injection without retraining backbone models, reducing iteration cycles from weeks to days at YouTube scale.

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#online-learning

@TensorTonic: in machine learning, the RBF kernel measures similarity between points. increasing gamma makes similarity fall faster w…

X AI KOLs Timeline ↗ · 2026-09-21 Cached

A promotional post for TensorTonic, an online platform for learning machine learning through coding practice, starting with an explanation of the RBF kernel.

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#online-learning

Optimal Randomized Proper Online Learning

arXiv cs.LG ↗ · 2026-09-21 Cached

This paper improves the optimal expected mistake bound for randomized proper online learning, showing it is O(L(H) log T), which is optimal up to a universal constant for worst-case classes.

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#online-learning

What Should We Ask Next? Retrieval-Aware Question Learning under Partial Evidence

arXiv cs.AI ↗ · 2026-09-21 Cached

The paper introduces RAVEL, a retrieval-aware online reinforcement learning framework for interactive person re-identification that optimizes question selection based on retrieval feedback to improve performance across multiple interaction rounds.

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#online-learning

Keet

Product Hunt ↗ · 2026-09-19 Cached

Keet is an educational platform launched on Product Hunt, offering interactive video courses on any topic with AI integration.

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#online-learning

Online Adaptive Kernel Mixing for Gaussian Process Decision Making

arXiv cs.LG ↗ · 2026-09-18 Cached

This paper introduces HACK GPs, a method that uses online learning with expert advice for kernel selection in Gaussian Processes, enhancing robustness in sequential decision-making tasks such as Bayesian optimization and active learning.

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#online-learning

The Free Inference Dimension: Complexity Measure for Zero-Collision Navigation under Hypothesis Mixtures

arXiv cs.LG ↗ · 2026-09-17 Cached

The paper introduces the Free Inference dimension, a combinatorial complexity measure for zero-collision navigation in meta-reinforcement learning under hypothesis mixtures, proving its relationship with VC-dimension and generalization bounds.

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#online-learning

Sparse MLLM Anchors, Dense Adaptation: Breaking the Self-Referential Loop in Wild Test-Time Adaptation

arXiv cs.AI ↗ · 2026-09-16 Cached

The paper introduces MASA, a method that uses frozen multimodal large language models to break the self-referential loop in wild test-time adaptation by providing structured semantic descriptions for more reliable adaptation.

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#online-learning

Online Gradient Computation for Warping Gaussian Process Transformations

arXiv cs.LG ↗ · 2026-09-16 Cached

This paper proposes an online method for warped Gaussian processes that jointly updates latent GP moments and optimizes warping parameters using exact recursive gradient computation.

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#online-learning

Online Bayesian Node Classification on Inductive Graphs under Distribution Shift

arXiv cs.LG ↗ · 2026-09-15 Cached

This paper proposes a variational Bayesian last layer method for graph neural networks to perform online node classification under distribution shift, achieving superior accuracy and uncertainty calibration compared to baselines.

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#online-learning

ReCAST: Reward Credit Assignment across Timesteps for Online Diffusion Reinforcement

arXiv cs.LG ↗ · 2026-09-15 Cached

ReCAST proposes a method for per-reward, timestep-dependent credit assignment in diffusion model fine-tuning, separating user preferences from temporal allocation to improve alignment and informativeness.

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#online-learning

@sauda_coder: 10 Free Content Creation Courses to Learn Online 1. Content Marketing – HubSpot http://academy.hubspot.com/courses/cont…

X AI KOLs Timeline ↗ · 2026-09-12 Cached

A curated list of 10 free online courses for content creation, covering topics such as content marketing, blogging, and monetization, offered by platforms like HubSpot and Alison.

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#online-learning

Dictoterix

Product Hunt ↗ · 2026-09-10 Cached

Dictoterix is a free language learning service that uses the dichotic method, playing native and target languages in different ears simultaneously to improve learning efficiency.

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#online-learning

Microsoft trained a 4B coding agent almost entirely with Reinforcement Learning, without a bigger teacher

Reddit r/ArtificialInteligence ↗ · 2026-09-10 Cached

Microsoft Research presents FrogNano, a 4B coding agent trained exclusively via reinforcement learning with online task synthesis, achieving competitive performance without distillation from larger models.

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#online-learning

Online Learning with LLM Experts from Limited Feedback

arXiv cs.LG ↗ · 2026-09-10 Cached

This paper proposes algorithms for adaptively routing prompts to LLM experts in an online setting with limited feedback, formulated as a bandit problem to minimize regret and maximize response quality.

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#online-learning

HyperTrace: Hypothesis-Based Preference Tracing for Online LLM Personalization

arXiv cs.CL ↗ · 2026-09-10 Cached

HyperTrace is a training-free framework for online LLM personalization that uses interpretable natural-language hypotheses to trace latent user preferences, improving response alignment and consistency.

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#online-learning

Online Learning with LLM Experts from Limited Feedback

Hugging Face Daily Papers ↗ · 2026-09-05 Cached

This paper formulates the adaptive routing of prompts to large language model experts as a contextual bandit problem with limited feedback, proposing algorithms that achieve sublinear regret and demonstrate efficient learning of high-quality routing strategies.

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#online-learning

@Jolyne_AI: Ouch, not bad—found a website for learning skills like Linux, Docker, cybersecurity, and more: LabEx. It's not just wat…

X AI KOLs Timeline ↗ · 2026-09-03

A tweet recommends LabEx, an online platform for hands-on learning in skills like Linux, Docker, and cybersecurity, featuring interactive environments and Chinese support.

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