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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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48 results for keyboard suggestions

Shared Keyboard design improves phase I clinical trials by borrowing information across doses.

problem Interim decisions based on current dose data may overlook signals from neighboring doses.
method Bayesian model-assisted design using Beta kernel process with kernel-weighted pseudo-counts.
result Significant improvements in identifying maximum tolerated dose and safety.

While invasively recorded brain activity is known to provide detailed information on motor commands, it is an open question at what level of detail information about positions of body parts can be decoded from non-invasively acquired signals. In this work it is shown that index finger positions can be differentiated fr…

2015-12-14abs ↗pdf ↗

A new transformer model corrects diacritics and typos in multiple languages.

problem Restoring diacritics and correcting typos in online communications.
method Employing a universal ByT5 transformer model trained on 12 languages, including Lithuanian.
result Achieves > 98% accuracy in diacritics restoration and typos correction.

BCI system improves word selection efficiency using sequential best-arm identification.

problem Conventional non-adaptive BCI paradigms lead to a lengthy learning process.
method Casted as sequence of best-arm identification tasks in multi-armed bandits, using pre-trained LLMs and STTS algorithm.
result Substantial empirical improvement in word selection efficiency demonstrated.

Deep reinforcement learning improves medical test suggestions.

problem Improving accuracy of disease diagnosis through better medical test recommendations.
method Formulated as a stage-wise Markov decision process, trained using reinforcement learning with a new action policy representation and exploration scheme.
result Significant improvement in disease diagnosis accuracy with better medical test suggestions.

SessionPath improves category suggestions in type-ahead search.

problem Improving precision and recall in eCommerce type-ahead suggestions.
method SessionPath uses session embeddings and a probability distribution model to predict facets.
result SessionPath outperforms count-based and neural models in eCommerce shops.

We describe a set of Gaussian Process based approaches that can be used to solve non-linear Ordinary Differential Equations. We suggest an explicit probabilistic solver and two implicit methods, one analogous to Picard iteration and the other to gradient matching. All methods have greater accuracy than previously sugge…

2014-08-17abs ↗pdf ↗

This paper proposes the use of wavelet methods to estimate U.S. core inflation. It explains wavelet methods and suggests they are ideally suited to this task. Comparisons are made with traditional CPI-based and regression-based measures for their performance in following trend inflation and predicting future inflation.…

2011-03-29abs ↗pdf ↗

Efficient algorithm for mobile health provides timely physical activity suggestions.

problem Inefficient reinforcement learning for mobile health settings.
method Contextual bandit algorithm with linear mixed effects model and hyper-parameter updating.
result Improves speed and accuracy by up to 99% and 56%.

Diversifies reply suggestions for IM systems using M-CVAE.

problem Improving diversity of automated reply suggestions in instant messaging systems.
method Formulated a generative latent variable model with Conditional Variational Auto-Encoder (M-CVAE) to diversify responses.
result Increased diversity by ~30-40% without significant impact on relevance.

We suggest using the max-norm as a convex surrogate constraint for clustering. We show how this yields a better exact cluster recovery guarantee than previously suggested nuclear-norm relaxation, and study the effectiveness of our method, and other related convex relaxations, compared to other clustering approaches.

2012-02-25abs ↗pdf ↗

Experiment shows cognitive biases impact human-AI collaboration, highlighting the need for diverse evaluator samples.

problem Cognitive biases affect human-AI collaboration, leading to suboptimal outcomes.
method Randomized experiment with 2,784 participants, manipulating AI suggestion quality, task burden, and financial incentives.
result Individual attitudes toward AI are the strongest predictor of performance, influencing accuracy and overcorrection.

Proposes a new query autocompletion method that maximizes retrieval performance.

problem Users often select suboptimal queries due to unknown best retrieval performance.
method Formulates query autocompletion as ranking item rankings, uses counterfactual learning.
result Empirical results show improved query suggestions for better retrieval performance.

We suggest an empirical model of investment strategy returns which elucidates the importance of non-Gaussian features, such as time-varying volatility, asymmetry and fat tails, in explaining the level of expected returns. Estimating the model on the (former) Lehman Brothers Hedge Fund Index data, we demonstrate that th…

2011-12-05abs ↗pdf ↗

The self-similar analysis of time series, suggested earlier by the authors, is applied to the description of market crises. The main attention is payed to the October 1929, 1987 and 1997 stock market crises, which can be successfully treated by the suggested approach. The analogy between market crashes and critical phe…

1997-10-30abs ↗pdf ↗

We extend the well-known Borromean and Brunnian rings to new higher order versions. Then we suggest an extension of the connection between Efimov states in cold gases and Borromean and Brunnian rings to these new higher order links. This gives rise to a whole new hierarchy of possible states with Efimov states at the b…

2010-12-13abs ↗pdf ↗

Comment on recent paper suggesting adversarially trained BNNs are more robust, finds no strong evidence.

problem Evaluating the robustness of adversarially trained Bayesian Neural Networks (BNNs) against adversarial attacks.
method Developed a new type of adversarial attack to incorporate the stochastic nature of BNNs, used to evaluate robustness.
result No strong evidence of higher robustness of adversarially trained BNNs.

It has been suggested in 1999 that a certain volume growth condition for geodesically complete Riemannian manifolds might imply that the manifold is stochastically complete. This is motivated by a large class of examples and by a known analogous criterion for recurrence of Brownian motion. We show that the suggested im…

2009-08-28abs ↗pdf ↗

Automated suggestions help train technicians diagnose incidents faster.

problem Manual and time-consuming incident diagnosis by train maintenance technicians.
method Developed and deployed a learning machine to suggest diagnostics to technicians.
result The model refines its accuracy through feedback from experts and uses feature engineering.

Develops a method for generating understandable and attainable counterfactual explanations for tabular data.

problem Ensuring counterfactual explanations are both interpretable and attainable for individuals.
method Combines quality measures with manifold learning techniques to generate counterfactuals that are both proximate and connected to regions of high data density.
result Proposes a framework (C-CHVAE) for generating attainable counterfactuals that are also interpretable.

Numerical computations suggest that each point on a certain optimized shape called the ideal trefoil is in contact with two other points. We consider sequences of such contact points, such that each point is in contact with its predecessor and call it a billiard. Our numerics suggest that a particular billiard on the i…

2011-03-18abs ↗pdf ↗

The study of the relation between the Weierstrass inducing formulae for constant mean curvature surfaces and the completely integrable euclidean nonlinear sigma-model suggests a connection among integrable sigma -models in a background and other type of surfaces. We show how a generalization of the Weierstrass represen…

2002-07-27abs ↗pdf ↗

Study suggests using information flow measures to target interventions in neural networks.

problem Identifying neural network edges that can be pruned to reduce bias.
method Used MM-information flow framework to measure and compare information flows about true labels and protected attributes, and evaluated pruning effects on bias reduction.
result Pruning edges with larger information flows about protected attributes reduces bias at the output.

New approach uses deep learning to control SAI for climate mitigation.

problem Catastrophic regional consequences of naive SAI control.
method Treats SAI as a high-dimensional control problem using Deep Reinforcement Learning (DRL).
result First application of DRL to climate sciences.

Recent developments in the understanding of N=2N=2 supersymmetric Yang-Mills theory in four dimensions suggest a new point of view about Donaldson theory of four manifolds: instead of defining four-manifold invariants by counting SU(2)SU(2) instantons, one can define equivalent four-manifold invariants by counting solution…

1994-11-15abs ↗pdf ↗

Study finds 'happiness' search data predicts stock returns, suggesting utility needs impact firm performance.

problem Investing in firms that meet societal utility needs.
method Used Google Trends data on 'happiness' search volume to predict stock returns.
result Happiness search exposure (HSE) explains future stock returns, particularly for big and value firms.

This study analyzes cryptocurrency market crashes using complex network analysis.

problem Identifying and understanding dynamics of cryptocurrency market crashes.
method Complex network analysis of cryptocurrency market during pre-crash, crash, and post-crash periods.
result Network density and clustering coefficient spike during crashes, indicating uninformed panic sell-off.

Study reveals XAI methods fail in neuroimaging, suggesting domain-specific adaptation.

problem Systematic failures of XAI methods in neuroimaging applications.
method Systematic comparison of XAI methods on 45,000 structural brain MRIs using a novel validation framework.
result Two widely used XAI methods (GradCAM and Layer-wise Relevance Propagation) fail to accurately explain neuroimaging data.

The following is an amalgamation of four preprints and some computer programs which together represent the current state of our investigations of higher order links. This investigation was motivated by questions discussed and raised in the first author's paper "New States of Matter Suggested by New Topological Structur…

2016-02-20abs ↗pdf ↗

New findings suggest deep generative models can misclassify outliers, requiring new evaluation methods.

problem Deep generative models often assign higher likelihood to outliers, challenging existing outlier detection methods.
method Analyzed the typical set and high-density region of DGMs, proposing a novel outlier test.
result Existing likelihood-based outlier tests may fail due to model calibration issues, not just misclassification.

Study improves understanding of what makes machine learning explanations human-interpretable.

problem Understanding what makes explanations human-interpretable in machine learning systems.
method Controlled human-subject experiments to identify regularizers for interpretability across three tasks.
result Cognitive chunks affect performance more than variable repetitions, suggesting common design principles.

Improved regression analysis using Padé approximants with new residuals and regularization.

problem Improving regression analysis with Padé approximants for accuracy and avoiding overfitting.
method New residuals in least squares method, system of linear equations for rational functions, Tikhonov regularization.
result Demonstrated efficiency in practical cases from physics and reliability theory.

We extend Relative Robust Portfolio Optimisation models to allow portfolios to optimise their distance to a set of benchmarks. Portfolio managers are also given the option of computing regret in a way which is more in line with market practices than other approaches suggested in the literature. In addition, they are gi…

2017-01-11abs ↗pdf ↗

The paper suggests new topological lower bounds for the number of zeros of closed 1-forms within a given cohomology class. The main new technical tool is the deformation complex, which allows to pass to a singular limit and reduce the original problem with a closed 1-form to a traditional problem with a Morse function.…

1999-03-23abs ↗pdf ↗

AI framework uses multi-omics data to personalize cancer treatment suggestions.

problem Leveraging AI for personalized cancer treatment based on complex patient characteristics.
method Modular machine learning framework trained on diverse multi-omics technologies.
result Superior performance in personalized counterfactual treatment suggestions.

Wedge product on deRham complex of a Riemannian manifold MM can be pulled back to H(M)H^*(M) via explicit homotopy, constructed using Green's operator, to give higher product structures. We prove Fukaya's conjecture which suggests that Witten deformation of these higher product structures have semiclassical limits as op…

2014-01-23abs ↗pdf ↗