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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.

168,742 papers · 148 categories

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68136203271 · May 202619922001200920172026
48 results for level four

Study shows how SL2\operatorname{SL}_2 Hitchin connection at level four behaves.

problem Understanding the behavior of SL2\operatorname{SL}_2 Hitchin connection at level four.
method Using Mumford-Welters connections and equivariant conformal embeddings, the connection's monodromy is shown to be finite.
result The monodromy of the SL2\operatorname{SL}_2 Hitchin connection at level four is finite.

Predicts coherence from quantum heat engine noise using machine learning.

problem Predicting coherence in quantum heat engines from nonequilibrium fluctuations.
method Developed a machine learning protocol using K-Nearest Neighbor (KNN) model.
result Machine learning successfully predicts coherence from quantum heat engine noise.

By evaluating the Burau representation at t=-1, we obtain a symplectic representation of the braid group. We define the congruence subgroups of the braid group to be the preimages of the principal congruence subgroups of the symplectic group. Our main result is that the level four congruence subgroup of the braid group…

2014-10-27abs ↗pdf ↗

New methods test correlation between network structure and node features.

problem Assessing correlation between network structure and node-level covariates.
method Four novel methods based on linear models and canonical correlation analysis.
result Theoretical guarantees and computational efficiency for testing network dependency.

Hierarchical reinforcement learning (HRL) has recently shown promising advances on speeding up learning, improving the exploration, and discovering intertask transferable skills. Most recent works focus on HRL with two levels, i.e., a master policy manipulates subpolicies, which in turn manipulate primitive actions. Ho…

2018-11-10abs ↗pdf ↗

The Milnor fibre of any isolated hypersurface singularity contains many exact Lagrangian spheres: the vanishing cycles associated to a Morsification of the singularity. Moreover, for simple singularities, it is known that the only possible exact Lagrangians are spheres. We construct exact Lagrangian tori in the Milnor …

2014-05-04abs ↗pdf ↗

We give a one parameter family of exceptional planar 5-webs. Each web is formed by four pencils of lines and by a foliation defined by the level curves of a function sn_k(x)sn_k(y) where sn_k denotes a Jacobi's elliptic function.

2004-07-15abs ↗pdf ↗

We consider here the problem of classifying orbits of an action of the dif- feomorphism group of 3-space on a tower of fibrations with P2-fibers that generalize the Monster Tower due to Montgomery and Zhitomirskii. As a corollary we give the first steps towards the problem of classifying Goursat 2-flags of small length…

2011-07-21abs ↗pdf ↗

This paper improves level generation using VAEs for coherent, logically following segments.

problem Generating coherent levels of non-fixed length and blending levels from different games.
method Sequential segment-based level generation using VAEs with a classifier for logical placement.
result Generated levels are more coherent and capable of blending levels from different games.

We present a new modeling technique for solving the problem of ecological inference, in which individual-level associations are inferred from labeled data available only at the aggregate level. We model aggregate count data as arising from the Poisson binomial, the distribution of the sum of independent but not identic…

2018-02-04abs ↗pdf ↗

Elliptic curves and braid groups linked through configuration spaces.

problem Understanding the relationship between elliptic curves and braid groups via configuration spaces.
method Constructing isomorphisms between configuration spaces and triples of elliptic curves, points, and holomorphic differentials.
result Unified exceptional sequences involving braid groups and automorphisms of free groups.

Energy is a limited resource which has to be managed wisely, taking into account both supply-demand matching and capacity constraints in the distribution grid. One aspect of the smart energy management at the building level is given by the problem of real-time detection of flexible demand available. In this paper we pr…

2016-05-06abs ↗pdf ↗

Paper proposes a deep subspace clustering method using multi-level representations.

problem Deep subspace clustering of images.
method Convolutional autoencoders with multiple fully-connected layers for multi-level representations, loss minimization with iterative updates.
result The method outperforms state-of-the-art methods on real-world datasets.

Adaptive batching improves Gaussian process surrogates for noisy level set estimation.

problem Learning the level set of noisy simulator responses.
method Developed four novel adaptive batching schemes for Gaussian process metamodels.
result Adaptive batching brings significant computational speed-ups with minimal loss of modeling fidelity.

Most modern neural machine translation (NMT) systems rely on presegmented inputs. Segmentation granularity importantly determines the input and output sequence lengths, hence the modeling depth, and source and target vocabularies, which in turn determine model size, computational costs of softmax normalization, and han…

2018-10-02abs ↗pdf ↗

We study the Hamiltonian vector field v=(f/w,f/z)v=(-\partial f/\partial w,\partial f/\partial z) on C2\mathbb C^2, where f=f(z,w)f=f(z,w) is a polynomial in two complex variables, which is non-degenerate with respect to its Newton's polygon. We introduce coordinates in four-dimensional neighbourhoods of the "points at infinity", in …

2011-07-11abs ↗pdf ↗

Researchers infer firm-level supply chain networks from sector-level data to assess systemic risk.

problem Estimating systemic risk in economic systems using firm-level data.
method Maximum-entropy algorithms applied to input-output tables and firm-level aggregate output data.
result The most realistic systemic risk content is retrieved by models incorporating disaggregated firm-specific inputs by sector.

Elliptic Chern characters and Atiyah-Witten formula generalized to double loop spaces.

problem Generalizing classical Atiyah-Witten formula to double loop spaces.
method Constructing elliptic Chern and Bismut-Chern characters, defining elliptic holonomy, and using equivariant twisted parallel transport.
result Established elliptic Atiyah-Witten formula on double loop space.

Level assessment for foreign language students is necessary for putting them in the right level group, furthermore, interviewing students is a very time-consuming task, so we propose to automate the evaluation of speaker fluency level by implementing machine learning techniques. This work presents an audio processing s…

2018-08-31abs ↗pdf ↗

This is the first of two articles in which we give a proof - for a broad class of four-manifolds - of Witten's conjecture that the Donaldson and Seiberg-Witten series coincide, at least through terms of degree less than or equal to c-2, where c is a linear combination of the Euler characteristic and signature of the fo…

2000-07-31abs ↗pdf ↗

DeepScalper uses RL to capture intraday trading opportunities, balancing risk and profit.

problem Capturing fleeting intraday trading opportunities in high-frequency markets.
method Dueling Q-network, reward function with hindsight bonus, encoder-decoder architecture, risk-aware auxiliary task.
result Significantly outperforms state-of-the-art baselines in financial criteria.

Study rigidifies geometry of electrostatic systems with specific tensor properties.

problem Investigating rigidity in electrostatic systems with specific tensor properties.
method Analyzing static Einstein--Maxwell spacetimes with harmonic (anti-)self-dual Weyl tensor.
result Gradient of lapse function is an eigenvector of Ricci tensor and manifold is locally conformally flat.

We find the optimal investment strategy for an individual who seeks to minimize one of four objectives: (1) the probability that his wealth reaches a specified ruin level {\it before} death, (2) the probability that his wealth reaches that level {\it at} death, (3) the expectation of how low his wealth drops below a sp…

2007-03-28abs ↗pdf ↗

In this paper we investigate the endogenous information contained in four liquidity variables at a five minutes time scale on equity markets around the world: the traded volume, the bid-ask spread, the volatility and the volume at first limits of the orderbook. In the spirit of Granger causality, we measure the level o…

2018-11-09abs ↗pdf ↗

One out of four children in India are leaving grade eight without basic reading skills. Measuring the reading levels in a vast country like India poses significant hurdles. Recent advances in machine learning opens up the possibility of automating this task. However, the datasets of children's speech are not only rare …

2019-11-27abs ↗pdf ↗

Unified benchmark for GLAD and GLOD methods across 35 datasets.

problem Gap between GLAD and GLOD research due to distinct evaluation setups.
method Comprehensive evaluation framework that unifies GLAD and GLOD.
result Multi-dimensional analyses of existing methods' strengths and limitations.

This study examines non-retail trading on Polymarket, revealing unique behavior patterns and structural limitations.

problem Lack of address-level quote-lifecycle data in Polymarket prediction markets.
method Empirical analysis of 13 million order-filled events using DBSCAN clustering on a six-feature fill-side vector.
result Non-retail behavior is uni-modal, contradicting previous archetypal hypotheses.

Paper compares AutoML methods for recommending classification algorithms.

problem Finding the best classification algorithm for a dataset.
method Four AutoML methods using Evolutionary Algorithms and CASH approach.
result EA-based methods, especially decision-tree induction, produce interpretable models.

The paper proposes selective forgetting for deep neural networks at a finer level than samples.

problem Selective forgetting of deep neural networks to handle outliers, poisoned data, or sensitive information.
method Formulated selective forgetting at a finer level than samples, introduced as an optimization problem on three criteria.
result Experimental results show the model can forget specific information for classification, improving accuracy in specific cases.

Study examines if LLMs' trading styles match real market behavior.

problem Lack of behavioral consistency in LLMs' trading strategies.
method Year-long simulations with LLMs, operationalizing behavioral finance drivers, and comparing with financial theory.
result LLMs' strategy switching is only partially consistent with behavioral finance theories.