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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.

168,695 papers · 148 categories

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5111621 · Jun 202019922001200920172026
48 results for spurious attractors

New study shows min-max algorithms can converge to non-stationary points.

problem Challenges in min-max optimization due to periodic cycles and spurious attractors.
method Analyzed state-of-the-art algorithms and heuristics in non-convex/non-concave problems.
result Spurious attractors can prevent min-max algorithms from reaching true optima.

DMs emerge from DenseAMs, transitioning from memorization to generalization.

problem Hindered memory retrieval in DenseAMs due to spurious states.
method Examined diffusion models through the lens of DenseAMs, focusing on their generative process.
result Identified a critical phase in DMs transitioning from memorization to generalization.

Paper analyzes coexisting hidden and self-excited attractors in an economic system.

problem Existence of coexisting hidden and self-excited attractors in economic systems.
method Integer and fractional order analysis of an economic system.
result Integer-order system exhibits multiple combinations of coexisting hidden and self-excited attractors.

The paper is focused on the existence problem of attractors for foliations. Since the existence of an attractor is a transversal property of the foliation, it is natural to consider foliations admitting transversal geometric structures. As transversal structures are chosen Cartan geometries due to their universality. T…

2017-03-22abs ↗pdf ↗

This paper classifies expanding attractors and non-transitive Anosov flows on specific knot and manifold spaces.

problem Classifying expanding attractors and non-transitive Anosov flows on specific knot and manifold spaces.
method Using the derived Anosov (DA) expanding attractor and the Franks-Williams manifold, the paper proves the uniqueness of these structures.
result The DA expanding attractor and the Franks-Williams non-transitive Anosov flow are the unique structures supported by N0N_0 and M0M_0 respectively.

The paper studies dimensions of attractors for modified Leray-alpha equation on various surfaces.

problem Investigate attractor dimensions of the modified Leray-alpha equation.
method Existence and uniqueness of weak solutions, global attractor existence, estimates for vorticity scalar equations, Kolmogorov flows.
result Established upper and lower bounds for Hausdorff and fractal dimensions of global attractors on S2\mathbb{S}^2 and T2\mathbb{T}^2.

A central challenge faced by memory systems is the robust retrieval of a stored pattern in the presence of interference due to other stored patterns and noise. A theoretically well-founded solution to robust retrieval is given by attractor dynamics, which iteratively clean up patterns during recall. However, incorporat…

2018-11-23abs ↗pdf ↗

In human perception and cognition, a fundamental operation that brains perform is interpretation: constructing coherent neural states from noisy, incomplete, and intrinsically ambiguous evidence. The problem of interpretation is well matched to an early and often overlooked architecture, the attractor network---a recur…

2019-06-08abs ↗pdf ↗

In this paper we focus on compacta KR3K \subseteq \mathbb{R}^3 which possess a neighbourhood basis that consists of nested solid tori TiT_i. We call these sets toroidal. In \cite{hecyo1} we defined the genus of a toroidal set as a generalization of the classical notion of genus from knot theory. Here we introduce the se…

2019-09-18abs ↗pdf ↗

Study analyzes Echo State Network parameters for Rossler attractor dynamics.

problem Understanding the influence of network type on Echo State Network performance.
method Experimental analysis of Echo State Network parameters using Rossler attractor.
result Exploration of how network type affects Echo State Network performance.

This paper studies closed 3-manifolds which are the attractors of a system of finitely many affine contractions that tile R3\mathbb{R}^3. Such attractors are called self-affine tiles. Effective characterization and recognition theorems for these 3-manifolds as well as theoretical generalizations of these results to hig…

2014-02-12abs ↗pdf ↗

In this paper we consider the realization of DE attractors by self-diffeomorphisms of manifolds. For any expanding self-map φ:MMφ:M\to M of a connected, closed pp-dimensional manifold MM, one can always realize a (p,q)(p,q)-type attractor derived from φφ by a compactly-supported self-diffeomorphsm of $\RR^{p+q}$, as long…

2008-11-25abs ↗pdf ↗

Removing spurious features can hurt model accuracy and disproportionately affect different groups.

problem Interference from spurious features in robust model performance across different groups.
method Characterization and analysis of spurious feature removal in noiseless overparameterized linear regression.
result Removal of spurious features can decrease accuracy and disproportionately affect different groups, even in balanced datasets.

SGD quickly learns a spurious XOR feature before the signal feature, revealing learning dynamics.

problem Over-reliance on spurious correlations in neural networks trained by SGD.
method Theoretical analysis of SGD on two-layer ReLU networks trained on XOR data.
result SGD learns the spurious feature first and exponentially fast, dominating the signal feature.

This research examines rare spurious correlations in neural networks and their impact on accuracy and privacy.

problem Rare spurious correlations in neural networks and their privacy risks.
method Introducing spurious patterns correlated with a fixed class to a few training examples, analyzing 2\ell_2 regularization and Gaussian noise.
result Rare spurious correlations can significantly impact neural network accuracy and privacy, and specific mitigation methods can be effective.

Motivated by the study in Morse theory and Smale's work in dynamics, the following questions are studied and answered: (1) When does a 3-manifold admit an automorphism having a knotted Smale solenoid as an attractor? (2) When does a 3-manifold admit an automorphism whose non-wandering set consists of Smale solenoids? T…

2004-03-25abs ↗pdf ↗

In this paper we study the Lorenz equations using the perspective of the Conley index theory. More specifically, we examine the evolution of the strange set that these equations posses throughout the different values of the parameter. We also analyze some natural Morse decompositions of the global attractor of the syst…

2018-12-12abs ↗pdf ↗

Learning three data points can generate all types of periodic orbits in a neural network.

problem Can learning three data points generate all types of periodic orbits in a neural network?
method Investigated a continuous one-dimensional map with period three in a random neural network in its thermodynamic limit.
result Almost all learned periods are unstable, and each network has its own characteristic attractors.

Unified Bayesian framework predicts cryptocurrency market dynamics and volatility.

problem Predicting cryptocurrency market trends and volatility.
method Bayesian framework based on potential field theory and Gaussian Process.
result Attractors and repellers from the potential field are reliable market indicators.

CLIP models robustness to spurious features is re-evaluated using a new dataset.

problem Existing robustness tests of CLIP models may not fully reflect their performance on spurious features.
method Crafted a new dataset (CounterAnimal) to reveal CLIP models' reliance on realistic spurious features.
result CLIP models are robust to spurious features learned from their training data, not ImageNet.

Study identifies and analyzes spurious correlations in data-driven models.

problem Spurious correlations in data-driven models are unreliable and hard to detect.
method Collect and analyze synthetic datasets generated from causal graphs to investigate spurious correlations.
result Patterns connecting spurious correlation hypotheses and model design choices were observed.

In this paper we study the cohomological Conley index of arbitrary isolated invariant continua for continuous maps f ⁣:URdRdf \colon U \subseteq \mathbb{R}^d \to \mathbb{R}^d by analyzing the topological structure of their unstable manifold. We provide a simple dynamical interpretation for the first cohomological Conley index…

2018-02-07abs ↗pdf ↗

Algorithm removes spurious concepts from neural network representations without harming task performance.

problem Spurious correlations hinder neural network out-of-distribution generalization.
method Iterative algorithm that identifies two orthogonal subspaces in neural network representation.
result Algorithm outperforms existing methods on computer vision and natural language processing benchmarks.

We analyze the dynamical properties of a tetrahedron transformation on the space of non-degenerate tetrahedra which can be identified with the non-compact globally symmetric 88-dimensional space $\mbox{Sl}(3,\mathbb{R}) / \mbox{So}(3,\mathbb{R})$. We establish the existence of a local attractor which coincides with th…

2017-08-28abs ↗pdf ↗

An iterated function system ΦΦ consisting of contractive similarity mappings has a unique attractor FRdF \subseteq \mathbb{R}^d which is invariant under the action of the system, as was shown by Hutchinson [Hut]. This paper shows how the action of the function system naturally produces a tiling T\mathcal{T} of the con…

2006-06-05abs ↗pdf ↗

Current OOD benchmarks overestimate model robustness to spurious correlations.

problem Spurious correlations degrade OOD performance, but benchmarks show the opposite.
method Analyze OOD datasets for spurious correlations and derive conditions for robustness.
result Current OOD benchmarks are misspecified and overestimate model robustness.

Mitigates biases in reward models using variational inference.

problem Spurious correlations in reward models that align large language models with human preferences.
method Formulates data-generating process, identifies non-spurious latent variables, and uses variational inference to recover them.
result Effective mitigation of spurious correlation issues, yielding more robust reward models.

AFR simplifies reducing reliance on spurious features, improving model performance.

problem Reducing reliance on spurious features for out-of-distribution generalization.
method Automatic Feature Reweighting (AFR) updates the model with a weighted loss.
result AFR improves model performance on benchmarks with minimal compute.

Let MM be a manifold or (more generally) a locally compact, metrizable ANR. If KK is an attractor for a flow in MM, with basin of attraction A(K)\mathcal{A}(K), it is well known that the inclusion i:KA(K)i : K \subseteq \mathcal{A}(K) is always a shape equivalence. In this paper we investigate to what extent this generaliz…

2015-11-20abs ↗pdf ↗

This paper explores loss landscapes of sparse neural networks, finding unique characteristics compared to dense networks.

problem Understanding the loss landscape of sparse neural networks, especially one-hidden-layer networks.
method Analyzes sparse networks with dense and sparse final layers, focusing on linear and non-linear models.
result Sparse networks can have no spurious valleys under certain conditions, but spurious valleys and minima can exist for wide sparse networks.

ERDMD discovers sparse, nonuniformly timed DMD models from chaotic attractors.

problem Discovering high-fidelity, nonuniformly timed DMD models from chaotic data.
method Entropic regression for nonlinear information flow detection, combined with multi-step DMD.
result ERDMD produces highly efficient and robust models with minimal complexity.