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78157235313 · May 202619922001200920172026
48 results for slice derivatives

In the 60's Levine proved that if RR is a slice knot, then on any genus gg Seifert surface for RR there is a gg component link JJ, called a derivative of RR, on which the Seifert form vanishes. Many subsequent obstructions to RR being slice are given in terms of slice obstructions of JJ. Many of these obstructi…

2015-11-23abs ↗pdf ↗

We show that every good boundary link with a pair of derivative links on a Seifert surface satisfying a homotopically trivial plus assumption is freely slice. This subsumes all previously known methods for freely slicing good boundary links with two or more components, and provides new freely slice links.

2018-07-15abs ↗pdf ↗

From Furuta's 108\frac{10}{8} theorem, we derive a smooth slicing obstruction for knots in S3S^3 using a spin 44-manifold whose boundary is 00-surgery on a knot. We show that this obstruction is able to detect torsion elements in the smooth concordance group and find topologically slice knots which are not smoothly sl…

2015-08-27abs ↗pdf ↗

We define an obstruction for a knot to be Z[Z]-homology ribbon, and use this to provide restrictions on the integers that can occur as the triple linking numbers of derivative links of knots that are either homotopy ribbon or doubly slice. Our main application finds new non-doubly slice knots. In particular this gives …

2018-02-02abs ↗pdf ↗

Study efficient iterative method for distribution matching using sliced optimal transport.

problem Efficiently match distributions using sliced optimal transport.
method Slice-matching scheme based on sliced optimal transport, with quantitative non-asymptotic rates derived.
result Derive quantitative non-asymptotic rates for convergence to target distribution.

We define an operation on homology B4{B}^4 which we call an nn-twist annulus modification. We give a new construction of smoothly slice knots and exotically slice knots via nn-twist annulus modifications. As an application, we present a new example of a smoothly slice knot with non-slice derivatives. Such examples we…

2015-12-01abs ↗pdf ↗

A new metric HSW derived from hierarchical Radon Transform addresses computational bottlenecks in sliced Wasserstein.

problem Computational inefficiency of sliced Wasserstein in high-dimensional settings with few supports.
method Hierarchical Radon Transform (HRT) and bottleneck projections to reduce projection number.
result HSW metric derived from HRT is computationally efficient and maintains metric properties.

We prove that the topological locally flat slice genus of large torus knots takes up less than three quarters of the ordinary genus. As an application, we derive the best possible linear estimate of the topological slice genus for torus knots with non-maximal signature invariant.

2015-09-25abs ↗pdf ↗

We define a set of "second-order" L^(2)-signature invariants for any algebraically slice knot. These obstruct a knot's being a slice knot and generalize Casson-Gordon invariants, which we consider to be "first-order signatures". As one application we prove: If K is a genus one slice knot then, on any genus one Seifert …

2008-08-11abs ↗pdf ↗

A derivative of an algebraically slice knot KK is an oriented link disjointly embedded in a Seifert surface of KK such that its homology class forms a basis for a metabolizer HH of KK. We show that for a genus three algebraically slice knot KK, the set $\{ \barμ_{\{γ_1,γ_2,γ_3\}}(123) - \barμ_{\{γ'_1,γ'_2,γ'_3\}}(…

2016-03-30abs ↗pdf ↗

A new method for comparing image probability measures using convolution operators.

problem Efficiently comparing images using conventional sliced Wasserstein methods.
method Proposed convolution sliced Wasserstein (CSW) methods with stride, dilation, and non-linear activation.
result CSW demonstrates favorable performance over conventional sliced Wasserstein in image comparison and deep generative modeling.

The paper explores statistical and topological properties of sliced probability divergences.

problem Understanding the topological, statistical, and computational consequences of slicing divergences.
method Deriving theoretical properties of sliced probability divergences, including metric axioms preservation and weak continuity.
result Sliced divergences share similar topological properties and have stable sample complexity.

A new method optimizes projection directions for sliced Wasserstein distances.

problem Finding informative projecting directions for sliced Wasserstein distances is computationally expensive.
method Amortized projection optimization to predict directions efficiently.
result Proposed amortized models improve generative modeling performance.

Sliced inverse regression (SIR) is a pioneer tool for supervised dimension reduction. It identifies the effective dimension reduction space, the subspace of significant factors with intrinsic lower dimensionality. In this paper, we propose to refine the SIR algorithm through an overlapping slicing scheme. The new algor…

2018-06-23abs ↗pdf ↗

Sharp bounds for max-sliced Wasserstein distances derived for empirical distributions.

problem Estimating the expected max-sliced Wasserstein distance between a probability measure and its empirical distribution.
method Banach space version and operator norm approach for upper bounds.
result Upper bounds for max-sliced Wasserstein distances are essentially matching and sharp up to a log factor.

We derive integral and sup-estimates for the curvature of stably marginally outer trapped surfaces in a sliced space-time. The estimates bound the shear of a marginally outer trapped surface in terms of the intrinsic and extrinsic curvature of a slice containing the surface. These estimates are well adapted to situatio…

2005-12-19abs ↗pdf ↗

Study knot invariants to answer questions about slice genus and clasp numbers.

problem Whether the difference between the four-dimensional clasp number and the slice genus can be arbitrarily large.
method Equivariant singular instanton theory and Chern--Simons functional.
result Answers a conjecture by Livingston about slicing numbers and provides a lower bound for the unoriented slice genus.

Proposes an energy-based sliced Wasserstein distance for improved probability measure comparison.

problem Inefficiencies and limitations in existing sliced Wasserstein distance approaches.
method Introduces an energy-based slicing distribution for better performance and stability.
result Demonstrates superior performance of the EBSW distance in various applications.

We produce infinite families of knots {Ki}i1\{K^i\}_{i\geq 1} for which the set of cables {Kp,1i}i,p1\{K^i_{p,1}\}_{i,p\geq 1} is linearly independent in the knot concordance group. We arrange that these examples lie arbitrarily deep in the solvable and bipolar filtrations of the knot concordance group, denoted by {Fn}\{F_n\} and $\{…

2018-06-16abs ↗pdf ↗

This work investigates the properties of Gaussian-smoothed sliced divergences for comparing distributions.

problem Comparing probability distributions while preserving privacy.
method Investigates the theoretical properties of Gaussian-smoothed sliced Wasserstein distance and generalized versions.
result Gaussian smoothed sliced Wasserstein distance converges with a rate of \(O(n^{-1/2})\).

Lower bounds for a knot invariant are derived using computations and cobordism inequality.

problem Calculating the concordance invariant s#s^{\#} for knots.
method Computation for torus knots, cobordism inequality of s#s^{\#}, and arguments for slice-torus invariants.
result Lower bounds for s#s^{\#} are derived for knots.

This work improves scalability of Wasserstein distances in high dimensions.

problem Scalability issues in computing Wasserstein distances in high dimensions.
method Empirical convergence rates, robustness to data contamination, and computational methods.
result Established fast rates and robust estimation risks for sliced Wasserstein distances.

Improves point-cloud reconstruction by optimizing projections with self-attention.

problem Inefficient and non-metric projection methods for sliced Wasserstein distances.
method Proposes distributional sliced Wasserstein distance with self-attention for permutation-invariant and metric optimization.
result Self-attention amortized distributional projection optimization achieves better performance in point-cloud reconstruction.

Empower efficient representation of distributions through moment-preserving methods.

problem Representing high-dimensional probability measures efficiently and accurately.
method Empower efficient representation of distributions through moment-preserving methods.
result Empowers efficient and accurate representation of high-dimensional probability measures.

Efficiently predicts optimal transport plans using sliced potentials.

problem Predicting optimal transport plans across multiple measure pairs efficiently.
method Regression-based and objective-based amortization strategies using sliced optimal transport potentials.
result Efficient and accurate prediction of optimal transport plans for various tasks.

In [HT], two of us constructed a closed oriented 4-dimensional manifold with fundamental group Z\Z that does not split off S1×S3S^1\times S^3. In this note we show that this 4-manifold, and various others derived from it, do not admit smooth structures. Moreover, we find an infinite family of 4-manifolds with exactly the…

2006-11-03abs ↗pdf ↗

Paper optimizes WGAN parameters for non-Gaussian data.

problem Optimizing parameters for non-Gaussian data in WGAN.
method Characterization of optimal solutions for population WGAN beyond LQG setting, using sliced Wasserstein framework.
result Closed-form optimal parameters for non-linear activation functions and non-Gaussian data derived.

We consider linear slices of the space of Kleinian once-punctured torus groups; a linear slice is obtained by fixing the value of the trace of one of the generators. The linear slice for trace 2 is called the Maskit slice. We will show that if traces converge `horocyclically' to 2 then associated linear slices converge…

2013-03-29abs ↗pdf ↗

A new method approximates the Sliced-Wasserstein distance without random projections.

problem Efficiently approximating the Sliced-Wasserstein distance for machine learning applications.
method Utilizing the concentration of measure phenomenon to develop a deterministic approximation.
result The approximation error goes to zero as the dimension increases, under a weak dependence condition.