We study partial-feedback online learning, where each instance admits a set of correct labels, but the learner only observes one correct label per round; any prediction within the correct set is counted as correct. This model captures settings such as language generation, where multiple responses may be valid but data provide only a single reference. We give a near-complete characterization of minimax regret for both deterministic and randomized learners in the set-realizable regime, i.e., in the regime where […]

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arXiv:2601.20876v1 Announce Type: new Abstract: We present BioNIC, a multi-layer feedforward neural network for emotion classification, inspired by detailed synaptic connectivity graphs from the MICrONs dataset. At a structural level, we incorporate architectural constraints derived from a single cortical column of the mouse Primary Visual Cortex(V1): connectivity imposed via adjacency masks, laminar organization, and graded inhibition representing inhibitory neurons. At the functional level, we implement biologically inspired learning: Hebbian synaptic plasticity with homeostatic regulation, Layer Normalization, data augmentation […]

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Hi all — I’m hoping for some perspective from people with more RL / game-AI experience than I have. I’m working on a small, deterministic 2-player abstract strategy game (perfect information, no randomness, forced captures/removals). The ruleset is intentionally compact, and human play suggests there may be non-obvious strategic depth, but it’s hard to tell without stronger analysis. Rather than jumping straight to a full AlphaZero-style setup, I’m interested in more modest questions first: How the game behaves […]

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Introduction Disclaimer: This article is a cross post from Pytorch Medium Blog Post. One of the most exciting advancements, that has pushed the frontier of the Artificial Intelligence (AI) in recent years, is Deep Reinforcement Learning (DRL). DRL belongs to the family of machine learning algorithms. It assumes that intelligent machines can learn from their actions similar to the way humans learn from experience. Over the recent years we could witness some impressive real-world applications of DRL. The […]

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arXiv:2602.22292v1 Announce Type: new Abstract: Peer review remains a cornerstone in academia, yet it frequently falls short in fostering joint progress and well-being. While peer review primarily emphasizes scientific rigor, it often lacks the empathy essential for supporting and encouraging all peers involved. In this experience report, I aim to highlight that peer review is a practice that demands both scientific care for quality and collegial welfare for the joint progress and well-being of all peers involved, including […]

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arXiv:2602.09127v1 Announce Type: new Abstract: Recent generative and tool-using AI systems can surface a large volume of candidates at low marginal cost, yet only a small fraction can be checked carefully. This creates a decoder-side bottleneck: downstream decision-makers must form reliable posteriors from many public records under scarce attention. We formalize this regime via Attention-Constrained Inference (ACI), in which a cheap screening stage processes $K$ records and an expensive verification stage can follow up on at most $B$ […]

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arXiv:2601.04608v1 Announce Type: cross Abstract: We study U.S. Treasury yield curve forecasting under distributional uncertainty and recast forecasting as an operations research and managerial decision problem. Rather than minimizing average forecast error, the forecaster selects a decision rule that minimizes worst case expected loss over an ambiguity set of forecast error distributions. To this end, we propose a distributionally robust ensemble forecasting framework that integrates parametric factor models with high dimensional nonparametric machine learning models through adaptive forecast […]

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arXiv:2604.09717v1 Announce Type: new Abstract: Character recognition is the fundamental part of an optical character recognition (OCR) system. Word recognition, sentence transcription, document digitization, and language processing are some of the higher-order activities that can be done accurately through character recognition. Nonetheless, recognizing handwritten Bangla characters is not an easy task because they are written in different styles with inconsistent stroke patterns and a high degree of visual character resemblance. The datasets available are usually limited in intra-class […]

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arXiv:2505.18269v4 Announce Type: replace-cross Abstract: We study the problem of selecting a subset from a large action space shared by a family of bandits, with the goal of achieving performance nearly matching that of using the full action space. Indeed, in many natural situations, while the nominal set of actions may be large, there also exist significant correlations between the rewards of different actions. In this paper we propose an algorithm that can significantly reduce the action space […]

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