arXiv research

Auto-detection system identifies safety issues in baby products from reviews.

We further study the incidence relations that arise from the various subtowers, known as Baby Monster, which exist within the $\mathbb{R}^{3}$-Monster Tower. This allows us to complete the $RVT$ class spelling rules. We also present a method of calculating the various Baby Monster that appear within the Monster Tower.

Enhances relational reasoning with multi-layer architecture.

Population growth (or decay) in a country can be due to various f socio-economic constraints, as demonstrated in this paper. For example, sexual intercourse is banned in various religions, during Nativity and Lent fasting periods. Data consisting of registered daily birth records for very long (35,429 points) time seri…

Accelerator boosts energy efficiency for MANNs on FPGAs.

This paper sets baselines for reading comprehension benchmarks, finding simple models often perform well.

The Monster tower, also known as the Semple tower, is a sequence of manifolds with distributions of interest to both differential and algebraic geometers. Each manifold is a projective bundle over the previous. Moreover, each level is a fiber compactified jet bundle equipped with an action of finite jets of the diffeom…

Paper improves preterm birth prediction using neural networks with noisy labels.

New algorithms minimize dynamic regret for strongly convex losses.

Machine reading using differentiable reasoning models has recently shown remarkable progress. In this context, End-to-End trainable Memory Networks, MemN2N, have demonstrated promising performance on simple natural language based reasoning tasks such as factual reasoning and basic deduction. However, other tasks, namel…

Paper proposes a method to recover accurate labels from partially valid data in multi-label learning.

We highlight a pitfall when applying stochastic variational inference to general Bayesian networks. For global random variables approximated by an exponential family distribution, natural gradient steps, commonly starting from a unit length step size, are averaged to convergence. This useful insight into the scaling of…

Graph-structured data appears frequently in domains including chemistry, natural language semantics, social networks, and knowledge bases. In this work, we study feature learning techniques for graph-structured inputs. Our starting point is previous work on Graph Neural Networks (Scarselli et al., 2009), which we modif…

MAC Net improves natural language question answering with data-driven reasoning.

We present a novel recurrent neural network (RNN) based model that combines the remembering ability of unitary RNNs with the ability of gated RNNs to effectively forget redundant/irrelevant information in its memory. We achieve this by extending unitary RNNs with a gating mechanism. Our model is able to outperform LSTM…

Synthetic learning improves neonatal brain MRI segmentation robustness.

Oeljeklaus-Toma (OT) manifolds are certain compact complex manifolds built from number fields. Conversely, we show that the fundamental group often pins down the number field uniquely. We relate the first homology to some interesting ideal. OT manifolds are never Kähler, but carry an LCK metric (locally conformally Käh…

BoSsNet learns language and knowledge separately, improving task-oriented dialog performance.

Fair quantile regression adjusts estimators to balance subpopulation quantiles.

Study compares AI and static analysis for detecting buffer overflows.

Proposes VILMAP for finding motifs and segmenting words in time series.

The paper studies hyperkähler structures and adapted complex structures using the Monge-Ampère equation.

New algorithms minimize dynamic regret in non-stationary online learning.

We can overcome uncertainty with uncertainty. Using randomness in our choices and in what we control, and hence in the decision making process, could potentially offset the uncertainty inherent in the environment and yield better outcomes. The example we develop in greater detail is the news-vendor inventory management…

Graph2Seq converts graph inputs to sequences with attention-based neural networks.

EMR learns to read and remember from streaming data for QA.

RUM improves RNN's long-term memory by using unitary matrices.

Study uses non-invasive sensors to assess microbial contamination in green salads.

This paper tackles quantizing memory-augmented neural networks, improving their performance and energy efficiency.

Introduces methods to approximate complex sets by simpler Euclidean spaces.

The paper studies a new type of submanifolds in product spaces.

The paper extends affine connection results to singular warped and twisted products.

Defines products for fibered corners manifolds, generalizing resolutions.

Characterizes metallic structures on product manifolds and provides conditions for warped products to be metallic.

Productivity and credit limits affect aggregate production in non-monotonic ways.

Einstein metrics on products are shown to be warped.

Uniform criterion for vanishing products in bounded cohomology.

ProductNet curates high-quality product datasets for better product understanding.

The paper studies affine connections on singular warped products and their curvature.

We refine the intersection product in homology to an equivariant setting, which unifies several known constructions. As an application, we give a common generalisation of the Chas-Sullivan string product on a manifold and the Chataur-Menichi string product on the classifying space by defining a string product on the Bo…

The article surveys recent results on warped and CR-warped product submanifolds in Kaehler manifolds.

New method compares geometric and standard cup products.

The paper examines Einstein doubly warped product manifolds with a semi-symmetric metric connection.

Generalizes warped product submersion to conformal case.

Model learns product vectors from baskets and browsing sessions for better complementary product recommendations.

The paper explores geometric properties of Riemannian warped product maps and their curvature.

In this article we obtain classification results on the quasi-product production functions in terms of the geometry of their associated graph hypersurfaces, generalizing in a new setting some recent results concerning basic production models. In particular, we obtain several results on the geometry of Spillman-Mitscher…

Constructing a conformal product structure on $S^3$ using the Reeb foliation.