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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.

168,657 papers · 148 categories

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125251376501 · Jun 202019922001200920172026
48 results for MOS prediction

MO-GP models fill gaps in biophysical data with across-domain info transfer.

problem Gap filling of biophysical parameters LAI and fAPAR over rice areas.
method Multi-output Gaussian Processes (MO-GP) based on Linear Model of Coregionalization (LMC).
result MO-GP models successfully predict biophysical variables even in high missing data regimes.

MO-PaDGAN generates diverse, high-performance designs with multiple metrics.

problem Challenges in generating diverse, high-performance designs with multiple metrics.
method MO-PaDGAN uses a new Determinantal Point Processes based loss function for probabilistic modeling of diversity and performances.
result MO-PaDGAN expands the design space towards high-performance regions and generates new designs with high diversity and performances.

New algorithm learns and unlearns from streaming data efficiently.

problem Continuous learning and unlearning from production data streams.
method Translated batch unlearning techniques to online setting using regret, sample complexity, and deletion capacity.
result Achieved logarithmic regret bound of O(lnT)\mathcal{O}(\ln{T}) for online unlearning.

MO-PaDGAN improves multi-objective optimization by generating diverse and high-performing designs.

problem Challenges in parameterizing engineering designs for multi-objective optimization.
method MO-PaDGAN uses a generative adversarial network with a Determinantal Point Processes loss function to address these challenges.
result MO-PaDGAN generates designs with improved performance and coverage, even surpassing training data.

We discuss a method to construct Dirac-harmonic maps developed by J.~Jost, X.~Mo and M.~Zhu in J.~Jost, X.~Mo, M.~Zhu, \emph{Some explicit constructions of Dirac-harmonic maps}, J. Geom. Phys. \textbf{59} (2009), no. 11, 1512--1527.The method uses harmonic spinors and twistor spinors, and mainly applies to Dirac-harmon…

2018-09-26abs ↗pdf ↗

New category theory for complex projective plane sections.

problem Defining multi-valued Morse homotopy for complex projective plane.
method Introducing multi-valued Morse homotopy category and showing equivalence to DG category of holomorphic vector bundles.
result Multi-valued Morse homotopy category is equivalent to DG category of holomorphic vector bundles.

Sample-Rank simplifies MO recommendations by sampling and ranking, improving revenue with stable conversion rates.

problem Multi-objective recommendations in online food ordering systems.
method Multi-goal sampling followed by ranking, reducing MO problem to LTR model.
result Significant lift in revenue (2.64%) with stable conversion rates, no drop in last-mile traversal.

A novel Bayesian optimization framework tackles multi-objective constrained problems.

problem Multi-objective optimization with constraints in engineering design.
method srMO-BO-3GP framework using three stacked Gaussian processes.
result Demonstrated effectiveness on benchmark functions and real thermomechanical model.

USeMOC framework reduces expensive simulations for MO optimization with constraints.

problem Efficiently optimizing multi-objective problems with constraints using expensive function evaluations.
method USeMOC framework uses surrogate models to identify promising candidates and selects the best based on uncertainty.
result USeMOC achieves more than 90% reduction in function evaluations for circuit optimization.

MO-CBO optimizes multiple outcomes in causal systems with minimal data.

problem Optimizing multiple outcomes in causal systems with limited data.
method Decomposes MO-CBO into multi-objective optimization tasks and uses relative hypervolume improvement for sequential intervention balancing.
result MO-CBO outperforms traditional multi-objective Bayesian optimization in causal settings.

In many environments, only a relatively small subset of the complete state space is necessary in order to accomplish a given task. We develop a simple technique using emergency stops (e-stops) to exploit this phenomenon. Using e-stops significantly improves sample complexity by reducing the amount of required explorati…

2019-12-03abs ↗pdf ↗

Develops a new feature theory for robust machine learning.

problem Creating robust machine learning features from training data.
method Stochastic tensor space feature theory with Karhunen-Loeve expansion and hierarchical subspaces.
result Dramatic increases in accuracy for predicting Alzheimer's disease stages.

Myopic optimization outperforms reinforcement learning in portfolio management, leading to lower returns and higher risks.

problem Reinforcement learning strategies in portfolio management yield lower or negative returns and higher risks compared to myopic optimization.
method Modeling execution/liquidation frictions with mark-to-market accounting, using Malliavin calculus to derive policy gradients and risk shadow price, and quantifying phantom profit.
result Myopic optimization outperforms reinforcement learning in portfolio management, leading to better returns and lower risks.

Developers of text-to-speech synthesizers (TTS) often make use of human raters to assess the quality of synthesized speech. We demonstrate that we can model human raters' mean opinion scores (MOS) of synthesized speech using a deep recurrent neural network whose inputs consist solely of a raw waveform. Our best models …

2016-11-28abs ↗pdf ↗

A self-transverse immersion of a smooth manifold M^{k+2} in R^{2k+2} has a double point self-intersection set which is the image of an immersion of a smooth surface, the double point self-intersection surface. We prove that this surface may have odd Euler characteristic if and only if k is congruent to 1 modulo 4 or k+…

2000-03-11abs ↗pdf ↗

The paper analyzes Random Search and introduces BLiN-MOS for bandit learning.

problem Understanding and optimizing hyperparameter tuning in metric measure spaces.
method Introducing scattering dimension to quantify performance, and developing BLiN-MOS for bandit learning.
result Random Search converges to optimal values with specific rates in noise-free and noisy environments.

We construct a pair of transverse genuine laminations on an atoroidal 3-manifold admitting transversely orientable uniform 1-cochain. The laminations are induced by the uniform 1-cochain and they are indeed the "straightening" of the coarse laminations defined in [Ca], by using minimal surface techniques. Moreover, whe…

2003-04-07abs ↗pdf ↗

Executing a basket of co-integrated assets is an important task facing investors. Here, we show how to do this accounting for the informational advantage gained from assets within and outside the basket, as well as for the permanent price impact of market orders (MOs) from all market participants, and the temporary imp…

2018-07-04abs ↗pdf ↗

New model handles missing data effectively in autoregressive models.

problem Handling missing data in autoregressive models.
method Reinterpret existing models through missing data lens, introduce principled framework for incomplete datasets, active information acquisition.
result MO-ARM consistently outperforms imputation baselines across real-world benchmarks.

We construct an extension of the Kontsevich integral of knots to knotted trivalent graphs, which commutes with orientation switches, edge deletions, edge unzips, and connected sums. In 1997 Murakami and Ohtsuki [MO] first constructed such an extension, building on Drinfel'd's theory of associators. We construct a step …

2008-11-27abs ↗pdf ↗

The generalized Chen's conjecture on biharmonic submanifolds asserts that any biharmonic submanifold of a non-positively curved manifold is minimal (see e.g., [CMO1], [MO], [BMO1], [BMO2], [BMO3], [Ba1], [Ba2], [Ou1], [Ou2], [IIU]). In this paper, we prove that this conjecture is false by constructing foliations of pro…

2010-06-09abs ↗pdf ↗

In this paper we study unitary braid group representations associated with Majorana Fermions. Majorana Fermions are represented by Majorana operators, elements of a Clifford algebra. The paper recalls and proves a general result about braid group representations associated with Clifford algebras, and compares this resu…

2017-10-12abs ↗pdf ↗

Using a combinatorial approach described in a recent paper of Manolescu, Ozsváth, and Sarkar we compute the Heegaard-Floer knot homology of all knots with at most 12 crossings as well as the ττ invariant for knots through 11 crossings. We review the basic construction of \cite{MOS}, giving two examples that can be wor…

2006-10-05abs ↗pdf ↗

Paper proposes a transfer learning approach for decentralized QoE estimation.

problem Challenges in QoE model development due to small datasets, user diversity, and IPR/privacy concerns.
method A transfer learning-based ML model training approach that allows decentralized local models to share generic indicators and customize them further.
result The approach shows advantages of stacking various generic and specific models with corresponding weight factors.

New methods improve neural directed link prediction across all sub-tasks.

problem Directed link prediction requires handling edge directionality and bidirectionality, not just edge existence.
method Proposes three strategies: Multi-Class Framework, Multi-Objective, and Scalarized approaches.
result Improved performance across all three sub-tasks of directed link prediction.

We present RUSLAN -- a new open Russian spoken language corpus for the text-to-speech task. RUSLAN contains 22200 audio samples with text annotations -- more than 31 hours of high-quality speech of one person -- being the largest annotated Russian corpus in terms of speech duration for a single speaker. We trained an e…

2019-06-26abs ↗pdf ↗

Let SgS_{g} denote the genus gg closed orientable surface. For kNk\in \mathbb{N}, a kk-system is a collection of pairwise non-homotopic simple closed curves such that no two intersect more than kk times. Juvan-Malnič-Mohar \cite{Ju-Mal-Mo} showed that there exists a kk-system on SgS_{g} whose size is on the order o…

2014-03-20abs ↗pdf ↗

NEMoTS improves time series analysis by deriving efficient, interpretable models.

problem Lack of comprehensive understanding and insightful explanations in time series analysis.
method Neural-enhanced Monte-Carlo Tree Search (NEMoTS) for symbolic regression.
result NEMoTS provides efficient and interpretable models for time series analysis.

A novel semi-supervised outlier detection model detects anomalies with few labels.

problem Efficiently detecting group anomalies with limited labeled data.
method RCC-Dual-GAN model that combines RCC and M-GAN components for semi-supervised outlier detection.
result Significantly improved accuracy in outlier detection with few labeled anomalies.

There are few known computable examples of non-abelian surface holonomy. In this paper, we give several examples whose structure 2-groups are covering 2-groups and show that the surface holonomies can be computed via a simple formula in terms of paths of 1-dimensional holonomies inspired by earlier work of Chan Hong-Mo…

2014-10-25abs ↗pdf ↗

MOMENT selects and estimates mixed-effects models using moment identities.

problem Selecting and estimating random-effects covariance matrix and fixed-effects coefficients in multiresponse linear mixed-effects models.
method MOMENT is a stage-wise moment-based framework that reduces the random-effects selection problem to a smooth constrained convex optimization problem.
result MOMENT performs competitively and can outperform separate univariate analyses for correlated responses.