We define a notion of Hempel distance for one-sided Heegaard splittings and show that the existence of alternate surfaces restricts distance for one-sided splittings in a manner similar to Hartshorn's and Scharlemann-Tomova's results for two-sided splittings. We also show that every geometrically compressible one-sided…
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48 results for “sides”
Paper explores how to use mixed types of side information for better recommendations.
problem Challenges in using heterogeneous side information for recommender systems.
method Proposes a framework to jointly capture flat and hierarchical side information.
result Demonstrates significant performance gains over state-of-the-art methods.
When a Dehn filled link manifold contains a geometrically incompressible one-sided surface, it is shown there is a unique boundary incompressible position that the surface can take in the link space. The proof uses a version of the sweep-out technique from two-sided Heegaard splitting theory. When applied to one-sided …
The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases and co-existing conditions. However, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient. Polypharmacy side effects emerge because of drug-drug interactions, in which activi…
Using basic properties of one-sided Heegaard splittings, a direct proof that geometrically compressible one-sided splittings of RP^3 are stabilised is given. The argument is modelled on that used by Waldhausen to show that two-sided splittings of S^3 are standard.
Proposes a new IPW-based ranking metric for two-sided markets.
problem Addressing bias in implicit user feedback in two-sided markets.
method Extends IPW estimator to two-sided markets, addressing position bias.
result Proposed estimator is unbiased for ground-truth ranking metric.
A new algorithm for competing agents in a two-sided market setting.
problem Decentralized competition between agents in a two-sided market with unknown valuations.
method UCB-D3 algorithm for UCB with Decentralized Dominant-arm Deletion.
result UCB-D3 is order optimal and achieves a new regret lower bound.
We study the geometry of oriented right-angled hexagons in H^4, the hyperbolic 4-space, via Clifford numbers or quaternions. We show how to augment alternate sides of such a hexagon so that for the non-augmented sides, we can define quaternion half side-lengths whose angular parts are obtained from half the Euler angle…
This work improves wireless network learning by using side-information about interference.
problem Improving online learning algorithms in wireless networks.
method Exploiting side-information like interference levels to improve learning algorithms.
result Improved learning algorithms achieve higher throughput with fewer samples.
This paper improves sample efficiency in noisy inductive matrix completion with side-information.
problem Improving sample efficiency in noisy inductive matrix completion with side-information.
method Nonconvex projected gradient descent algorithm with spectral initialization.
result Achieves linear convergence and stable recovery at a sample complexity governed by the effective side-information dimension.
This paper offers a characterization of fundamental limits on the classification and reconstruction of high-dimensional signals from low-dimensional features, in the presence of side information. We consider a scenario where a decoder has access both to linear features of the signal of interest and to linear features o…
Let be a closed orientable surface of genus and a simple closed nonseparating curve in . Let denote a left handed Dehn twist about . A \textit{fractional power} of of \textit{exponent} $\fraction{\ell}{n}$ is an $h \in \Mod(S_g)$ such that . Unlike a root of a $t…
Generalization Bounds for Learning with Linear, Polygonal, Quadratic and Conic Side Knowledgestat.ML
In this paper, we consider a supervised learning setting where side knowledge is provided about the labels of unlabeled examples. The side knowledge has the effect of reducing the hypothesis space, leading to tighter generalization bounds, and thus possibly better generalization. We consider several types of side knowl…
The polypharmacy side effect prediction problem considers cases in which two drugs taken individually do not result in a particular side effect; however, when the two drugs are taken in combination, the side effect manifests. In this work, we demonstrate that multi-relational knowledge graph completion achieves state-o…
A deep neural network based architecture was constructed to predict amino acid side chain conformation with unprecedented accuracy. Amino acid side chain conformation prediction is essential for protein homology modeling and protein design. Current widely-adopted methods use physics-based energy functions to evaluate s…
In this paper we prove an extrinsic one-sided curvature estimate for disks embedded in with constant mean curvature which is independent of the value of the constant mean curvature. We apply this extrinsic one-sided curvature estimate in [24] to prove to prove a weak chord arc type result for these disks…
Very often features come with their own vectorial descriptions which provide detailed information about their properties. We refer to these vectorial descriptions as feature side-information. In the standard learning scenario, input is represented as a vector of features and the feature side-information is most often i…
Oil markets profoundly influence world economies through determination of prices of energy and transports. Using novel methodology devised in frequency domain, we study the information transmission mechanisms in oil-based commodity markets. Taking crude oil as a supply-side benchmark and heating oil and gasoline as dem…
Paper uses SDP for community detection with side information.
problem Community detection in graphs with additional non-graph data.
method Formulates SDP relaxation for maximum likelihood node labeling with side information.
result SDP achieves same exact recovery threshold as maximum likelihood with side information.
In the closed, non-Haken, hyperbolic class of examples generated by (2p,q) Dehn fillings of Figure 8 knot space, the geometrically incompressible one-sided surfaces are identified by the filling ratio p/q and determined to be unique in all cases. When applied to one-sided Heegaard splittings, this can be used to classi…
Semi-Supervised Node Classification by Graph Convolutional Networks and Extracted Side Informationcs.LG
This paper improves node classification using graph structure and side information.
problem Improving node classification in semi-supervised scenarios.
method Combines graph convolutional networks with extracted side information.
result The proposed model achieves higher prediction accuracy.
Study removes singularities from area-minimizing surfaces.
problem Removal of singularities from area-minimizing surfaces.
method Extending results on area-minimizing cones to handle isolated singularities.
result Isolated singularities can be locally perturbed away on the minimizing side.
Study of Bayes optimal learning in high-dimensional linear regression with network side information.
problem Bayes optimal learning in high-dimensional linear regression with network side information.
method Introduce a Reg-Graph model and an iterative AMP algorithm for Bayes optimality under general conditions.
result Characterization of the limiting mutual information between latent signal and data observed.
Online algorithm for binary matrix completion with side information.
problem Matrix completion with side information for binary matrices.
method Online algorithm with mistake and regret bounds.
result Novel mistake and regret bounds of the form .
Analyzes semi-characteristics on specific manifolds, proving a vanishing theorem.
problem Analyzing semi-characteristics on certain manifolds.
method Combines assembly maps and Hodge theorem perspectives.
result Proves an Atiyah type vanishing theorem.
On Many Body System Interactionscond-mat.quant-gas
We discuss possible relationships between geometric and topological interactions on one side and physical interactions on the other side.
The study of geodesics on hyperbolic surfaces with angle and side bounds.
problem Understanding the geometric properties of geodesics on hyperbolic surfaces.
method Analyzing the angles and sides of polygons formed by geodesics, based on their lengths.
result Bounds for angles and sides of polygons formed by geodesics, depending only on geodesic lengths.
Tensor completion requires fewer samples with weak side information.
problem Tensor completion with limited samples and side information.
method Algorithm utilizing weak side information to reduce sample complexity.
result Consistent estimator with samples for any small constant .
On the One-sided Convergence of Adam-type Algorithms in Non-convex Non-concave Min-max Optimizationcs.LG
Adam-type optimizers show one-sided convergence in GAN training, not reaching critical points.
problem Theoretical understanding of Adam-type optimizers in non-convex non-concave min-max optimization.
method Empirical and theoretical analysis of Adam-type algorithms' convergence in GAN training.
result Adam-type algorithms converge to one-sided first order stationary points under the one-sided MVI condition.
We address the problem of Compressed Sensing (CS) with side information. Namely, when reconstructing a target CS signal, we assume access to a similar signal. This additional knowledge, the side information, is integrated into CS via L1-L1 and L1-L2 minimization. We then provide lower bounds on the number of measuremen…
VEC-SBM detects communities using side information like texts and images.
problem Community detection in social networks with side information.
method Proposes a novel algorithm based on iterative refinement techniques.
result Optimally recovers latent communities with side information.
Improves robust transfer learning with side information.
problem Addressing environmental shift in MDPs with side information.
method Estimate-centered uncertainty sets with side information integration.
result Improved robust policy with reduced sub-optimality gap.
Algorithm identifies optimal stable matching in uncertain two-sided markets.
problem Sequential learning in two-sided markets with unknown preferences.
method Pure exploration approach with elimination-based algorithms exploiting partial preference information.
result Identification of pervasive stable matching for optimal stable matching identification.
Mining discriminative subgraph patterns from graph data has attracted great interest in recent years. It has a wide variety of applications in disease diagnosis, neuroimaging, etc. Most research on subgraph mining focuses on the graph representation alone. However, in many real-world applications, the side information …
The stability and the index of complete one-sided minimal surfaces of certain three-dimensional Riemannian manifolds with positive scalar curvature are studied.
Framework for robust matrix estimation with side information.
problem High-dimensional matrix estimation with restrictive structure.
method Flexible framework decomposing matrix into four components: interaction, row, column, and residual.
result Improved imputation accuracy and treatment-effect estimation with side information.
In this paper, we propose a model-based clustering method (TVClust) that robustly incorporates noisy side information as soft-constraints and aims to seek a consensus between side information and the observed data. Our method is based on a nonparametric Bayesian hierarchical model that combines the probabilistic model …
Optimizes arm selection with side information in Gaussian bandits.
problem Optimizing arm selection with side information in Gaussian bandits.
method Constructs an LP-based asymptotic instance-dependent lower bound on the regret and develops the first known asymptotically optimal algorithm.
result First known asymptotically optimal algorithm for Gaussian bandits with side information.
nnLDA combines neural and probabilistic methods for better topic modeling with side information.
problem Lack of integration of auxiliary information in traditional topic models.
method nnLDA integrates side information through a neural prior mechanism, optimizing both neural and probabilistic components.
result nnLDA outperforms traditional models in topic coherence, perplexity, and classification.
Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biology, and document analysis, among other areas. In many domains, there is additional information that can assist in prediction. For example, wh…
Deep learning predicts drug side-effects from molecular graphs.
problem Predicting drug side-effects from molecular structures.
method Recurrent Graph Neural Networks for multi-class multi-label graph-focused classification.
result Improved classification capability compared to previous methods.
Study on the regularity of -Gauss curvature flow near flat interfaces.
problem Regularity of -Gauss curvature flow near flat interfaces.
method Analysis of convex hypersurface near the interface.
result Regularity of the convex hypersurface near the interface.
Efficiently estimates distributed mean with side information, near-optimal and universal.
problem Distributed mean estimation with side information in communication constrained settings.
method Wyner-Ziv estimators for communication and computation efficiency.
result Near-optimal and universal recovery guarantees for distributed optimization and compression.
AdaDPS uses side information to improve private adaptive optimization.
problem Private adaptive optimization methods degrade when training with differential privacy.
method AdaDPS uses non-sensitive side information to precondition gradients.
result AdaDPS reduces the amount of noise needed for similar privacy guarantees, improving optimization performance.
Proposes a framework for fairness in two-sided marketplaces.
problem Achieving fairness in two-sided marketplaces.
method Developed an end-to-end framework for fairness constraints from both sides of the marketplace, including dynamic aspects.
result Efficacy of the proposed framework demonstrated through simulations.
Integrates side information for robust portfolio optimization.
problem Portfolio optimization under uncertainty and side information.
method Distributionally robust optimization with optimal transport ambiguity set.
result The problem can be reformulated as a finite-dimensional optimization problem.
New approach optimizes dynamic decisions with side info.
problem Optimizing decisions under uncertainty with additional data.
method Combines machine learning with robust optimization.
result Proves asymptotic optimality and achieves significant improvements.
We establish two-sided bounds for the complexity of two infinite series of closed orientable 3-dimensional hyperbolic manifolds, the Lobell manifolds and the Fibonacci manifolds.