arXiv research

T-BFA targets and misleads specific DNN inputs to a chosen output.

FlipOut prunes neural networks by flipping weights' signs, achieving high sparsity.

New methods train neural networks without changing weights, achieving similar or higher performance.

This paper uses the technology of weighted and regular triangulations to study discrete versions of the Laplacian on piecewise Euclidean manifolds. Regular triangulations are studied in some detail, including flip algorithms. The Laplacian is then studied as an operator on functions of the vertices as a generalized wei…

Study flip graphs for surfaces of infinite type, finding uncountably many connected components.

Finite subgraphs in flip graphs ensure unique surface embeddings.

Study of flip graphs and their automorphism groups for infinite-type surfaces.

Study shows flipping a small subset of labels can severely damage machine learning models.

Study of skateboard flips as continuous curves in $SO(3)$ group.

Proof of existence and uniqueness of weighted Voronoi-Delaunay on polyhedral surfaces.

Neural networks have been criticized for their lack of easy interpretation, which undermines confidence in their use for important applications. Here, we introduce a novel technique, interpreting a trained neural network by investigating its flip points. A flip point is any point that lies on the boundary between two o…

Flip symmetry on knot diagrams affects Khovanov homology.

Novel defense algorithm improves SVMs against data poisoning attacks.

The flip graph and arc complex of a surface are shown to have finite rigidity.

Efficiently poisons offline RLHF models by flipping preference labels.

New examples show flip distance and polyhedron triangulation numbers differ, with ratio close to 3/2.

We prove that every injective simplicial map $\mathcal{F}(S) \to \mathcal{F}(S')$ between flip graphs is induced by a subsurface inclusion $S\to S'$, except in finitely many cases. This extends a result of Korkmaz--Papadopoulos which asserts that every automorphism of the flip graph of a surface without boundary is ind…

We prove that for a given flat surface with conical singularities, any pair of geometric triangulations can be connected by a chain of flips.

We introduce a notion of cross-flips: local moves that transform a balanced (i.e., properly $(d+1)$-colored) triangulation of a combinatorial $d$-manifold into another balanced triangulation. These moves form a natural analog of bistellar flips (also known as Pachner moves). Specifically, we establish the following the…

This paper is about the geometry of flip-graphs associated to triangulations of surfaces. More precisely, we consider a topological surface with a privileged boundary curve and study the spaces of its triangulations with n vertices on the boundary curve. The surfaces we consider topologically fill this boundary curve s…

We consider geometric triangulations of surfaces, i.e., triangulations whose edges can be realized by disjoint locally geodesic segments. We prove that the flip graph of geometric triangulations with fixed vertices of a flat torus or a closed hyperbolic surface is connected. We give upper bounds on the number of edge f…

Geodesics count exponentially between triangulations of surfaces with enough topology.

Identifies minimal training subset to flip a prediction.

In order to model volatile real-world network behavior, we analyze phase-flipping dynamical scale-free network in which nodes and links fail and recover. We investigate how stochasticity in a parameter governing the recovery process affects phase-flipping dynamics, and find the probability that no more than q% of nodes…

Let $Σ$ be a compact surface. We prove that the set of surface cubications modulo flips, up to isotopy, is in one-to-one correspondence with $\Z/2\Z\oplus H_1(Σ,\Z/2\Z)$.

Study finds flipped classrooms improve student self-concept, enjoyment, but not exam scores.

Study quasisymmetric maps on hyperbolic plane boundaries.

We study flip-graphs of triangulations on topological surfaces where distance is measured by counting the number of necessary flip operations between two triangulations. We focus on surfaces of positive genus $g$ with a single boundary curve and $n$ marked points on this curve; we consider triangulations up to homeomor…

Using existing technology, we prove a Masur-Minsky style distance formula for flip- graph distance between two triangulations, expressed as a sum of the distances of the projections of these triangulations into arc graphs of the suitable subsurfaces of S.

We investigate a type of distance between triangulations on finite type surfaces where one moves between triangulations by performing simultaneous flips. We consider triangulations up to homeomorphism and our main results are upper bounds on distance between triangulations that only depend on the topology of the surfac…

Deep Partition Aggregation defends against poisoning attacks with provable certificates.

Deep learning models have been criticized for their lack of easy interpretation, which undermines confidence in their use for important applications. Nevertheless, they are consistently utilized in many applications, consequential to humans' lives, mostly because of their better performance. Therefore, there is a great…

The paper solves pentagon equations using triangulations and edge transformations.

New method makes machine learning models robust to label flipping attacks.

Study evaluates data augmentation methods for prostate cancer detection in MRI.

Graph convolutional networks (GCNs) are vulnerable to perturbations of the graph structure that are either random, or, adversarially designed. The perturbed links modify the graph neighborhoods, which critically affects the performance of GCNs in semi-supervised learning (SSL) tasks. Aiming at robustifying GCNs conditi…

We explore several families of flip-graphs, all related to polygons or punctured polygons. In particular, we consider the topological flip-graphs of once-punctured polygons which, in turn, contain all possible geometric flip-graphs of polygons with a marked point as embedded sub-graphs. Our main focus is on the geometr…

Unified routing and arbitrage with concave continuation.

Many machine learning systems rely on data collected in the wild from untrusted sources, exposing the learning algorithms to data poisoning. Attackers can inject malicious data in the training dataset to subvert the learning process, compromising the performance of the algorithm producing errors in a targeted or an ind…

The study examines flip-graphs of non-orientable surfaces and their diameters.

Improves bit error tolerance in RRAM-based BNNs without overfitting.

The paper explores orthogeodesics on hyperbolic surfaces and their integer traces.

This paper explores using nonlinear control for robust logarithmic growth in coin flipping games.

Paper proposes NeuroAttack to undermine SNNs security through bit-flips.

Double pants decompositions were introduced in our paper "Double pants decompositions of 2-surfaces" (Mosc. Math. J. 11 (2011), no. 2, 231-258, arXiv:1005.0073), together with a flip-twist groupoid acting on these decompositions. It was shown that flip-twist groupoid acts transitively on a certain topological class of …

Adaptive dropout and regularization are shown to be dual in linear networks.

Any two triangulations of a closed surface with the same number of vertices can be transformed into each other by a sequence of regular flips, provided the number of vertices exceeds a number N depending on the surface. Examples show that in general N is bigger than the minimal number of vertices of a triangulation. Th…

Over the past two decades, several consistent procedures have been designed to infer causal conclusions from observational data. We prove that if the true causal network might be an arbitrary, linear Gaussian network or a discrete Bayes network, then every unambiguous causal conclusion produced by a consistent method f…