Paper proposes a method for cross-lingual sentiment classification using distributed word representations.
problem Cross-lingual sentiment classification with strict one-to-one word mapping limitations.
method Uses distributed word representations to learn meaningful one-to-many mappings for pivot words.
result Method outperforms state-of-the-art in cross-lingual sentiment classification.
Proposes a method to generate diverse translations by conditioning on target domain.
problem NMT models lack diversity in translations, even with search algorithms.
method Condition the decoder on a latent variable representing target domain, generated by a target encoder.
result Generated diverse translations without affecting performance or training time.
Framework estimates multiple plausible solutions with uncertainty measures.
problem Machine learning models need to propose multiple plausible solutions with meaningful uncertainty.
method Discrete latent variables model one-to-many mappings, allowing effective conditional probability estimation.
result Framework outperforms state-of-the-art in uncertainty estimation and is practical.
A novel method for comparing graphs of different sizes using Wasserstein distance.
problem Comparing non-aligned graphs of varying sizes.
method Optimal transport in graph comparison framework, solving a one-to-many assignment problem.
result Significant improvements in graph alignment and classification tasks.
Paper tackles large-scale optimal transport and mapping estimation.
problem Learning optimal maps between large distributions.
method Two-step approach: first, stochastic dual regularized OT; second, Monge map estimation.
result The method scales better with large samples and converges to optimal maps.
SR-NAM maps low-res images to multiple high-res images realistically.
problem Mapping low-resolution images to multiple high-resolution images realistically.
method SR-NAM using Non-Adversarial Mapping (NAM) technique and a degradation model.
result Realistic degradation and down-sampling of high-resolution images.
New algorithm radVI improves variational inference by optimizing radial profiles.
problem Gaussian approximations often fail to capture the radial profile of complex distributions.
method Optimizes over radial profiles in variational inference, providing theoretical guarantees.
result Theoretical convergence guarantees for radVI, improving over existing VI methods.
We improve conditional VAEs by incentivizing informative latent variables.
problem Structured-prediction tasks with one-to-many mappings.
method Modify latent variable model and introduce a multimodal prior.
result Significantly higher generalisation capability demonstrated on various datasets.
Stochastic binary hidden units in a multi-layer perceptron (MLP) network give at least three potential benefits when compared to deterministic MLP networks. (1) They allow to learn one-to-many type of mappings. (2) They can be used in structured prediction problems, where modeling the internal structure of the output i…
New approach improves cross-domain recommendation for sparse target domains.
problem Cross-domain recommendation challenges with sparse target domains.
method Guided neural collaborative filtering with domain-invariant components across dense and sparse domains.
result Effective and scalable approach demonstrated on public and Visa datasets.
LostGANs generate realistic images from reconfigurable layouts and styles.
problem Learning generative models for realistic images from reconfigurable layouts and styles.
method End-to-end training of GANs with two new components: mask maps and ISLA-Norm.
result State-of-the-art performance on COCO-Stuff and Visual Genome datasets.
Hybrid model predicts product designs from target characteristics.
problem Designing new products with unknown target characteristics is expensive and time-consuming.
method Formulated as conditional density estimation, solved with a deep hybrid generative-discriminative model.
result Predicts optimal design parameters for any target in a single step.
IH-GAN models cellular structures accurately and improves structural performance.
problem Optimizing variable-density cellular structures with multiscale design challenges.
method Conditional deep generative model (IH-GAN) for property-to-geometry mapping using implicit function parameterization.
result Generates unit cells with high accuracy and improves structural performance.
Conditional Text Generation has drawn much attention as a topic of Natural Language Generation (NLG) which provides the possibility for humans to control the properties of generated contents. Current conditional generation models cannot handle emerging conditions due to their joint end-to-end learning fashion. When a n…
Transactional network data can be thought of as a list of one-to-many communications(e.g., email) between nodes in a social network. Most social network models convert this type of data into binary relations between pairs of nodes. We develop a latent mixed membership model capable of modeling richer forms of transacti…
The paper addresses statistical inference in matching markets with dependent missingness.
problem Statistical inference for two-sided matching markets with matching-induced dependence.
method Non-convex algorithm based on Grassmannian gradient descent, debiasing and projection framework.
result Near-optimal entrywise convergence rates for various matching mechanisms.
A VAE model predicts material properties and microstructures.
problem Building forward and inverse structure-property linkages in materials science.
method Combines VAE with regression, using a two-level prior and multi-modal Gaussian mixture.
result The model achieves accurate forward and inverse predictions of material properties and microstructures.
A new method handles mismatched data in multivariate regression.
problem Handling mismatched data in multivariate linear regression.
method Two-stage approach: first stage estimates parameters, second stage estimates permutation.
result Permutation recovery conditions become less stringent with increasing number of responses.
Modified Hungarian algorithm solves special OT problems efficiently.
problem Computing empirical Wasserstein distance in independence tests.
method Modified Hungarian algorithm for special OT problems.
result The modified algorithm solves special OT problems with complexity O(m2n). Proposes SLCVAE to improve text diversity by self-labeling.
problem KL-Vanishing problem in CVAE for diverse text generation.
method Explicit optimizing objective to guide encoder towards best encoder, using a labeling network.
result Improves text diversity while maintaining comparable accuracy.
The conditional-mean barrier helps diagnose deterministic surrogates missing uncertainty.
problem Uncertainty in deterministic surrogates for complex systems.
method Developed diagnostics to locate the conditional-mean barrier and prove its necessity for distributional objectives.
result Crossing the barrier requires a loss that scores distributions, not point predictions.
MINN-SA enhances cancer detection using TCR sequences with better interpretability.
problem Challenges in detecting cancers using TCR sequences due to one-to-many correspondence.
method Multiple Instance Neural Networks based on Sparse Attention (MINN-SA).
result MINN-SA achieves highest AUC scores on 10 cancer types compared to existing MIL approaches.
Transformer learns shipping costs more accurately than traditional methods.
problem Inaccurate shipping cost estimates lead to poor financial decisions.
method Proposes Rate Card Transformer (RCT) using self-attention to encode shipping information.
result Cost predictions made by RCT have 28.82% less error compared to GBDT models.
The article explores the mapping class group using unicellular maps and provides filtrations.
problem Understanding the structure of the mapping class group.
method Using unicellular maps and surgeries, the article describes the mapping class group.
result Provides filtrations of the mapping class group.
Constructs a moment map flow for isotropic maps on surfaces.
problem Understanding isotropic maps on surfaces and their properties.
method Develops a Kähler moment map geometry and a modified moment map flow.
result Polyhedral modified moment map flow induces a strong deformation retraction.
Deep learning classifies seven types of maps for better access.
problem Efficiently accessing the right map type from digital maps.
method Used deep convolutional neural networks to classify seven types of maps.
result Deep learning can accurately classify different types of maps.
The paper constructs biharmonic maps between spheres using polynomial maps.
problem Creating biharmonic maps between spheres.
method Using harmonic homogeneous polynomial maps of different degrees to generate proper biharmonic maps.
result Established a method for constructing proper biharmonic product maps.
Both bi-harmonic map and f-harmonic map have nice physical motivation and applications. In this paper, by combination of these two harmonic maps, we introduce and study f-bi-harmonic maps as the critical points of the f-bi-energy functional 21∫Mf∣τ(φ)∣2dvg. This class of maps generalizes both …
Generic pseudo-Anosov mapping classes in mapping class groups.
problem Understanding the prevalence of pseudo-Anosov mapping classes.
method Proving genericity with respect to specific notions of genericity.
result Pseudo-Anosov mapping classes are generic in mapping class groups.
Paper constructs maps for sutured monopole Floer homology.
problem None explicitly stated in the abstract.
method Constructs gluing and cobordism maps for sutured monopole Floer homology.
result Developed mathematical tools for sutured monopole Floer homology.
The paper generalizes Reeb spaces for special generic maps and lifts smooth functions.
problem Constructing lifts of smooth maps, especially Morse functions.
method Defining and generalizing quotient maps onto Reeb spaces of special generic maps and constructing lifts.
result Lifts of Morse functions can be constructed using the generalized maps.
Research explores real algebraic realization of round fold maps of codimension -1.
problem Real algebraic realization of round fold maps of codimension -1.
method Generalizes canonical projections of unit spheres to round fold maps and discusses their real algebraic realization.
result Developed new studies in real algebraic geometry focusing on round fold maps of codimension -1.
Study shows pure mapping classes can generate pseudo-Anosov mapping classes with certain conditions.
problem Understanding when pure mapping classes generate pseudo-Anosov mapping classes.
method Analyzing products of a given mapping class and powers of pure mapping classes, deriving an explicit constant.
result Almost all pure mapping classes generate pseudo-Anosov mapping classes when their powers exceed a certain constant.
The paper derives Liouville theorems for various generalized maps on Riemannian manifolds.
problem Deriving Liouville theorems for generalized maps on Riemannian manifolds.
method Using conservation laws and monotonicity formulas, the paper derives Liouville theorems for different types of maps under various conditions.
result The paper establishes Liouville theorems for several types of generalized maps, including φ-F harmonic maps, φ-F symphonic maps, and φ-F-V-harmonic maps. This paper shows semi-equivelar toroidal maps are vertex-transitive covers.
problem Understanding the relationship between semi-equivelar and vertex-transitive toroidal maps.
method Proving semi-equivelar toroidal maps are quotients of vertex-transitive toroidal maps.
result Each semi-equivelar toroidal map has a finite vertex-transitive cover.
Paper defines and studies Clairaut warped product Riemannian maps.
problem Understanding the geometry of specific Riemannian maps.
method Identify geodesic conditions, derive conditions for Clairaut maps, and calculate curvature.
result Found conditions for a warped product Riemannian map to be Clairaut.
Study shows no boundary maps for certain groups.
problem Existence of boundary maps for hierarchically hyperbolic spaces.
method Analysis of right-angled Artin groups and mapping class groups.
result Negative results on boundary maps for some groups.
The paper explores unique continuation properties for polyharmonic maps between Riemannian manifolds.
problem Investigating unique continuation principles for polyharmonic maps.
method Analyzing critical points of higher order functionals to prove extensions of known results in harmonic and biharmonic cases.
result Proving extensions of unique continuation principles for k-harmonic maps.
The hyperelliptic mapping class group has been studied in various contexts within topology and algebraic geometry. What makes this study tractable is that there is a surjective map from the hyperelliptic mapping class group to a mapping class group of a punctured sphere. The more general family of superelliptic mapping…
This paper constructs real algebraic maps that are topologically special generic maps.
problem Constructing smooth maps in differential topology and real algebraic geometry.
method Constructs real algebraic maps that are topologically special generic maps.
result Real algebraic maps are topologically special generic maps.
Derives stress-energy tensor for polyharmonic maps.
problem Characterizing polyharmonic maps between Riemannian manifolds.
method Derives stress-energy tensor and uses it to characterize polyharmonic maps.
result Characterizes polyharmonic maps, focusing on triharmonic maps.
The paper constructs gluing maps for harmonic maps between Riemannian manifolds.
problem Constructing harmonic maps between Riemannian manifolds.
method Gluing construction of extended harmonic maps.
result Construction of gluing maps for harmonic maps under specific conditions.
Characterizes a general range decreasing group homomorphism.
problem Understanding range decreasing group homomorphisms in the entire mapping group.
method Characterization of a general range decreasing group homomorphism.
result Computes a particular class of homomorphisms and identifies all range decreasing group homomorphisms on specific mapping groups.
The paper examines HM-tensional and HS-tensional maps between Riemannian manifolds.
problem Analyzing tension fields of maps between Riemannian manifolds.
method Investigating harmonic maps and harmonic sections as tension fields.
result Characterization and properties of HM-tensional and HS-tensional maps. The paper proves a Liouville theorem for specific harmonic maps with free boundary.
problem Analyzing harmonic maps with free boundary conditions.
method Developed Liouville theorem for φ-F-symphonic, φ-F-harmonic, and φ-ΦS,p,ε harmonic maps. result Established Liouville theorem for the specified harmonic maps with free boundary.
Dirac-harmonic maps are uncoupled under certain conditions.
problem Understanding the uncoupling of Dirac-harmonic maps.
method Critical points of a super-symmetric energy functional, with focus on harmonic maps.
result Dirac-harmonic maps are uncoupled under minimality assumption.
Paper preserves properties of mappings through generic mappings.
problem Preserving properties of mappings in higher dimensions.
method Composing generic generalized distance-squared mappings.
result Non-singular or injective properties preserved.
We introduce slant Riemannian maps from Riemannian manifolds to almost Hermitian manifolds as a generalization of slant immersions, invariant Riemannian maps and anti-invariant Riemannian maps. We give examples, obtain characterizations and investigate the harmonicity of such maps. We also obtain necessary and sufficie…