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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.

169,341 papers · 148 categories

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112225337449 · Jun 202019922001200920182026
48 results for logarithmic-time complexity

Optimal unimodal fitting for linear loss functions in a sequential, efficient manner.

problem Optimal unimodal transformation of univariate model scores under linear loss functions.
method Proposes a sequential approach to estimate the optimal rectangular fit for observed samples with each new sample.
result Sequential approach achieves optimal efficiency with logarithmic time complexity per iteration.

Logarithmic-time schedules boost large-scale language model training efficiency.

problem Improving performance and efficiency in large-scale language model training.
method Designing time-varying hyperparameters (β1,β2,λ)(β_1, β_2, λ) for AdamW, specifically logarithmic-time scheduling with damping mechanisms.
result ADANA optimizer achieves up to 40% compute efficiency compared to tuned AdamW, with gains persisting as model scale increases.

CMT efficiently manages memory by inserting and querying memories in logarithmic time.

problem Managing large memory stores efficiently for quick access and updates.
method Designing a Contextual Memory Tree (CMT) that inserts and retrieves memories in logarithmic time.
result CMT improves classification algorithms and image-captioning tasks, demonstrating better computational efficiency.

This paper tackles reinforcement learning in large action spaces, presenting a method that embeds actions in a continuous space and uses approximate nearest-neighbor methods.

problem Current reinforcement learning methods struggle with environments having large numbers of discrete actions, making them inapplicable to many real-world tasks.
method The approach embeds actions in a continuous space and uses approximate nearest-neighbor methods for efficient training.
result The proposed method enables reinforcement learning to be applied to large-scale learning problems previously intractable with current methods.

Optimal algorithms for mixable losses in dynamic environments with reduced redundancy.

problem Online optimization of mixable loss functions in a dynamic environment.
method Introduce online mixture schemes with polynomial and logarithmic time complexities.
result Achieves optimal redundancy up to a constant multiplicity gap.

Oracle-efficient algorithms reduce combinatorial semi-bandit regret to logarithmic time.

problem Scalability issue in combinatorial semi-bandit problems due to high combinatorial optimization costs.
method Oracle-efficient frameworks that minimize oracle queries while maintaining tight regret guarantees.
result Achieved ildeO(T) ilde{O}(\sqrt{T}) regret with O(loglogT)O(\log\log T) oracle queries for worst-case linear rewards.

Classical algorithms approximate quantum dynamics using subsampling.

problem Simulating quantum mechanical systems efficiently on classical computers.
method Randomized numerical linear algebra and the Nyström method for approximating matrix exponentials.
result Classical algorithms can efficiently simulate quantum computations under specific conditions.

Study shows polynomial-width neural networks can closely approximate infinite-width networks in polynomial time.

problem Approximating dynamics of polynomial-width neural networks with infinite-width networks.
method Bounding approximation gap through a differential equation governed by mean-field dynamics, considering local Hessian.
result Polynomially many neurons are sufficient to closely approximate mean-field dynamics.

pLSTM tackles long-range language modeling and computer vision tasks with parallelizable linear source transition mark networks.

problem Challenges of existing recurrent architectures in handling sequences and multi-dimensional data.
method Introduces pLSTM, a parallelizable linear source transition mark network for linear graphs and DAGs, addressing vanishing/exploding activation/gradient issues.
result pLSTM outperforms Transformers in long-range tasks like arrow-pointing extrapolation and image size extrapolation.

Study competition in OTC CDS market through CCP and interdealer choice models.

problem Analyze competition dynamics in OTC credit default swap market.
method Developed models for CCP choice and interdealer counterpart selection using semi-supervised learning and game theory.
result Introduced novel metrics and algorithms for understanding market dynamics.

Study on complex line fields on almost-complex manifolds, proving existence conditions.

problem Existence of linearly independent complex line fields on almost-complex manifolds.
method Prove necessary and sufficient conditions for the existence of one, two, or three fields over certain manifolds.
result Necessary and sufficient condition for the existence of complex line fields over certain manifolds.

Study complex deformations of compact complex surfaces in Calabi-Yau four-folds.

problem Explaining why complex and Cayley deformations of a compact complex surface are the same.
method Study complex deformations of compact complex submanifolds of Calabi-Yau manifolds.
result Prove that the moduli space of complex deformations of any compact complex embedded submanifold of a Calabi-Yau manifold is a smooth manifold.

This research explores complex-valued neural networks and their implementation.

problem The challenges of implementing complex-valued neural networks and their potential for non-complex data.
method Detailed theory and implementation of CVNN, including Wirtinger calculus, complex backpropagation, and modules like complex layers and activation functions. Python implementation using cvnn toolbox.
result Demonstrates the potential of CVNN for non-complex data through simulations.

The paper defines and constructs almost complex blow-ups on 4D almost complex manifolds.

problem Existence and uniqueness of almost complex blow-ups on almost complex manifolds.
method Definition and construction of almost complex blow-ups, proving their existence and uniqueness.
result Existence and uniqueness of almost complex blow-ups on 4D almost complex manifolds.

Study L2L^2 Hilbert complexes on complex manifolds.

problem Analyse L2L^2 Hilbert complexes on complex manifolds.
method Define and study L2L^2 Aeppli-Bott-Chern Hilbert complex; examine properties on various manifolds; use self-adjoint extensions of differential operators.
result Kernels of operators on compact Hermitian manifolds are isomorphic to Aeppli or Bott-Chern cohomology.

Odd m-fold connected sums of complex projective spaces admit almost complex structures.

problem Existence of almost complex structures on connected sums of complex projective spaces.
method Analyzing the m-fold connected sum m#CP2nm\#\mathbb{C}\mathbb{P}^{2n} for m odd or even.
result Only odd m-fold connected sums of complex projective spaces admit almost complex structures.

Study Hodge-de Rham numbers for almost complex 4-manifolds, extending properties from complex surfaces.

problem Understanding Hodge-de Rham numbers for almost complex 4-manifolds.
method Introduced and studied Hodge-de Rham numbers, extending properties from complex surfaces.
result All Hodge-de Rham numbers for compact almost complex 4-manifolds are determined by the cohomology, except for one (the irregularity).

Proposes a Complex Transformer for complex-valued sequence modeling.

problem Lack of deep learning models for complex-valued data.
method Develops a Complex Transformer using transformer backbone with specialized attention and encoder-decoder networks.
result Achieves state-of-the-art performance on complex-valued datasets.

Unified complexity measure for learning theory improves risk bounds.

problem Improving risk bounds in learning theory for various estimators.
method Introduces a new complexity measure interpolating between Rademacher, KL-divergence, and NML complexities.
result Bounded excess risk in terms of the new complexity measure.

The paper constructs complex structures on hypersurfaces in hyperkahler manifolds.

problem No specific problem stated; focuses on construction of structures.
method Construction of complex metric structures on hypersurfaces in hyperkahler manifolds.
result The construction of complex structures on hypersurfaces in hyperkahler manifolds.

A Sasaki-like almost contact complex Riemannian manifold is defined as an almost contact complex Riemannian manifold which complex cone is a holomorphic complex Riemannian manifold. Explicit compact and non-compact examples are given. A canonical construction producing a Sasaki-like almost contact complex Riemannian ma…

2014-02-21abs ↗pdf ↗

Study Sp(n)Sp(n)-orbits in complex and ΣΣ-complex subspaces of Hermitian quaternionic vector spaces.

problem Characterize Sp(n)Sp(n)-orbits in Grassmannians of complex and ΣΣ-complex subspaces.
method Decompose subspaces into 4-dimensional complex addends and 2-dimensional totally complex subspace. Use properties of isoclinic subspaces and principal angles.
result Determine full set of invariants for Sp(n)Sp(n)-orbits in GrR(2k,4n)Gr^\R(2k,4n).

Study on invariant almost complex structures on real flag manifolds.

problem Existence of invariant almost complex structures on real flag manifolds.
method Analysis of real flag manifolds associated to split real forms of complex simple Lie algebras.
result Some real flag manifolds do not admit invariant almost complex structures.

Tree complex linked to polyhedral shapes like associahedra and cyclohedra.

problem Understanding the structure of mapping class groups and complex dynamics.
method Characterizing associahedra and cyclohedra using planar tree embeddings and barycentric subdivision.
result Tree complex is a barycentric subdivision of a polyhedral cell complex made of associahedra and cyclohedra.