A new method trains deep neural networks for open set domain adaptation without negative open set difference.
arXiv research
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The aim of unsupervised domain adaptation is to leverage the knowledge in a labeled (source) domain to improve a model's learning performance with an unlabeled (target) domain -- the basic strategy being to mitigate the effects of discrepancies between the two distributions. Most existing algorithms can only handle uns…
New bounds on inscribed triangles in arbitrary planar domains.
This paper reviews information theory in open-world machine learning.
Study on covering probability of random balls in bounded open sets.
Sharp bounds on hyperbolic metrics in Ptolemaic spaces are derived.
Often, when dealing with real-world recognition problems, we do not need, and often cannot have, knowledge of the entire set of possible classes that might appear during operational testing. In such cases, we need to think of robust classification methods able to deal with the "unknown" and properly reject samples belo…
The VC-dimension of a set system is a way to capture its complexity and has been a key parameter studied extensively in machine learning and geometry communities. In this paper, we resolve two longstanding open problems on bounding the VC-dimension of two fundamental set systems: -fold unions/intersections of half-s…
End-to-end PGL framework tackles open-set domain shift.
Can certain shapes be drawn with a pencil and eraser?
Linear contextual bandit is an important class of sequential decision making problems with a wide range of applications to recommender systems, online advertising, healthcare, and many other machine learning related tasks. While there is a lot of prior research, tight regret bounds of linear contextual bandit with infi…
We consider the problem of online planning in a Markov Decision Process when given only access to a generative model, restricted to open-loop policies - i.e. sequences of actions - and under budget constraint. In this setting, the Open-Loop Optimistic Planning (OLOP) algorithm enjoys good theoretical guarantees but is …
A classical result due to Blaschke states that for every analytic self-map of the open unit disk of the complex plane there exists a Blaschke product such that the zero sets of and agree. In this paper we show that there is an analogue statement for critical sets, i.e. for every analytic self-map of…
Abstract reviews known and open questions on spaces with lower Ricci bounds.
For each Cantor set C in , all points of which have bounded local genus, we show that there are infinitely many inequivalent Cantor sets in with complement having the same fundamental group as the complement of C. This answers a question from Open Problems in Topology and has as an application a simple c…
A coordinate cone in R^n is an intersection of some coordinate hyperplanes and open coordinate half-spaces. A semi-monotone set is a defnable in an o-minimal structure over the reals, open bounded subset of R^n such that its intersection with any translation of any coordinate cone is connected. This can be viewed as a …
Upper bound for conjugate radius in open manifolds with scalar curvature and spectrum constraints.
We show that an entire branched cover of finite distortion cannot have a compact branch set if its distortion satisfies a certain asymptotic growth condition. We furthermore show that this bound is strict by constructing an entire, continuous, open and discrete mapping of finite distortion which is piecewise smooth, ha…
The study extends curvature bounds to non-smooth spaces and proves stability of mean curvature.
Let (M,g) be a compact Riemannian spin manifold. The Atiyah-Singer index theorem yields a lower bound for the dimension of the kernel of the Dirac operator. We prove that this bound can be attained by changing the Riemannian metric g on an arbitrarily small open set.
We give lower bounds for the fundamental tone of open sets in submanifolds with locally bounded mean curvature in , where is an -dimensional complete Riemannian manifold with radial sectional curvature . When the immersion is minimal our estimates are sharp. We also show that …
Learning linear predictors with the logistic loss---both in stochastic and online settings---is a fundamental task in machine learning and statistics, with direct connections to classification and boosting. Existing "fast rates" for this setting exhibit exponential dependence on the predictor norm, and Hazan et al. (20…
Open category detection is the problem of detecting "alien" test instances that belong to categories or classes that were not present in the training data. In many applications, reliably detecting such aliens is central to ensuring the safety and accuracy of test set predictions. Unfortunately, there are no algorithms …
New SVM margin bound improves generalization in machine learning.
In 1938, Tarski proved that a formula is not intuitionistically valid if, and only if, it has a counter-model in the Heyting algebra of open sets of some topological space. In fact, Tarski showed that any Euclidean space R^n with n >= 1 suffices, as does e.g. the Cantor space. In particular, intuitionistic logic cannot…
Consider a domain D in R^3 which is convex (possibly all R^3) or which is smooth and bounded. Given any open surface M, we prove that there exists a complete, proper minimal immersion f : M --> D. Moreover, if D is smooth and bounded, then we prove that the immersion f : M --> D can be chosen so that the limit sets of …
We first show that for a bounded pseudoconvex domain with a manifold quotient of finite-volume in the sense of Kahler-Einstein measure, the identity component of the automorphism group of this domain is semi-simple without compact factors. This partially answers an open question in [Fra95]. Then we apply this result in…
New sample complexity bounds for linear predictors and neural networks, focusing on initialization.
Paper resolves open problems on sample complexity in binary hypothesis testing.
Limits of manifolds with Kato bound on Ricci curvature are rectifiable.
The study examines spectral properties of the Laplacian on forms for open Riemannian manifolds.
We give lower bounds for the fundamental tone of open sets in minimal submanifolds immersed into warped product spaces of type , where . We also study the essential spectrum of these minimal submanifolds.
We observe that the maximal open set of constant curvature k in a Riemannian manifold with curvature bounded below or above by k has a convexity type property, which we call "two-convexity". This statement is used to prove a number of rigidity statements in comparison geometry.
The set of Clifford bundles of bounded geometry over open manifolds can be endowed with a metrizable uniform structure. For one fixed bundle we define the generalized component $\gencomp (E)$ as the set of Clifford bundles which have finite distance to . If , are the associated generalized Dirac ope…
The abstract discusses embedding manifolds in open books and contact structures.
Reduces bounded loss learning to binary classification.
In this note, we investigate upper bounds of the Neumann eigenvalue problem for the Laplacian of a bounded domain (with smooth boundary) in a given complete (not compact a priori) Riemannian manifold with Ricci bounded below . For this, we use test functions for the Rayleigh quotient subordinated to a family of open se…
New research shows exponential lower bounds for planning in MDPs with linearly-realizable optimal action-value functions.
Study shows area-minimizing submanifolds are mostly rough, not smooth.
For and a bounded, convex, nonempty, open set let be the -capacitary curvature measure (generated by the closure of ) on the unit circle . This paper shows that such a problem of prescribing on a planar convex domain: "Given a finite…
Novel approach to universal online learning for bounded losses, closing open problems.
Consider a sequence of minimal varieties M_i in a Riemannian manifold N such that the boundary measures are uniformly bounded on compact sets. Let Z be the set of points at which the areas of the M_i blow up. We prove that Z behaves in some ways like a minimal variety without boundary: in particular, it satisfies the s…
New approach for online learning with adaptive adversaries, simpler and more effective.
Study fine Pólya-Szegő inequalities in metric spaces with applications.
The paper proves properties of open manifolds with positive isotropic curvature.
Improved bounds for neural network approximations of functions.
In [J.Birman, V.Gebhardt, J.Gonzalez-Meneses, Conjugacy in Garside groups I: cyclings, powers and rigidity] authors asked: (open question 2) is the size of USS of a rigid pseudo-Anosov braid is bounded above by some polynomial in the number of strands and the braid length? We answer this question in the negative.
The study proves that sets with constant nonlocal curvature are composed of equal balls under certain conditions.