New method improves generics KBs by 80% precision.
problem Inferring new facts about generics from noisy KBs.
method Knowledge guided tensor factorization and taxonomy guided active learning.
result State-of-the-art results on two generics KBs (80% precise).
New neural KB representation speeds up reasoning with large symbolic knowledge bases.
problem Efficiently reasoning with large symbolic knowledge bases.
method Sparse-matrix reified knowledge base, enabling fully differentiable, scalable neural modules.
result Competitive performance on KB completion and semantic parsing benchmarks.
New dataset and methods for inferring missing entity types in knowledge bases.
problem Inferring missing entity type instances in knowledge bases.
method Automatic evaluation methodology, uses internal KB and external Wikipedia information.
result Global objective methods outperform baseline methods in KB completion.
New method improves KB completion by predicting unseen relations.
problem KB completion with improved multi-hop inference.
method Recursive neural network (RNN) for composing multi-hop relations.
result Improves KB completion by 11% over traditional methods.
A new query embedding method improves KB performance on complex queries.
problem QE systems disagree with deductive reasoning on some queries.
method A novel QE method more faithful to deductive reasoning.
result Better performance on complex queries to incomplete KBs.
Solves TOD systems' query annotation problem without explicit annotations.
problem Training TOD systems without explicit KB query annotation.
method Reinforcement learning (RL) and pipelined approach for query prediction and system training.
result Improved RL agent with modifications for TOD tasks.
Develops a method for constructing KBs with tunable precision for subjective and factual attributes.
problem Complexity in measuring subjective attributes complicates precision estimation in KBs.
method Probabilistically models user consensus with respect to each entity-attribute pair, using neural networks to fit the model.
result Learned models can successfully control KB's precision and outperform baselines in attribute prediction.
Proposes a new PBO method with theoretical guarantees.
problem Optimizing expensive functions in parallel with noisy evaluations.
method Randomized Kriging Believer (KB) based on KB heuristic.
result Randomized KB achieves Bayesian expected regret guarantees.
BoSsNet learns language and knowledge separately, improving task-oriented dialog performance.
problem End-to-end neural networks struggle with KB changes in task-oriented dialogs.
method Encoder-decoder architecture with Bag-of-Sequences memory.
result BoSsNet outperforms state-of-the-art models with >10% improvement on bAbI OOV test sets.
Paper tackles non-stationary kernelized bandits with near-optimal algorithm.
problem Minimizing regret in a time-varying reward function.
method Near-optimal algorithm with a novel restarting phased elimination with random permutation (R-PERP).
result Regret upper bound matches the lower bound, making the algorithm near-optimal.
Efficient neural models for complex multi-hop reasoning tasks.
problem Complex multi-hop reasoning tasks in large knowledge bases.
method Differentiable neural models using symbolic knowledge bases, with a new operation for multi-hop template construction.
result Simple neural models achieve competitive performance on multi-hop reasoning tasks.
This paper tackles open problem of tight bounds for KBs with Bernoulli rewards.
problem Open problem of tight bounds for Kernelized Bandits with Bernoulli rewards.
method Focus on Bernoulli model, not subgaussian noise, and optimize function in RKHS.
result Open problem remains unsolved in this context.
Proposes OpenKI for better web-scale knowledge extraction and alignment.
problem Combining OpenIE and KB for web-scale knowledge extraction and alignment.
method Instance-level inference using neighborhood information from KB and OpenIE extractions, with attention mechanisms.
result Significantly improves performance on OpenIE extractions and semi-structured data.
We study the regret minimization problem in the novel setting of generalized kernelized bandits (GKBs), where we optimize an unknown function f∗ belonging to a reproducing kernel Hilbert space (RKHS) having access to samples generated by an exponential family (EF) reward model whose mean is a non-linear function $μ(…
We show that Sol3×E1-manifolds are Seifert fibred, with general fibre the torus, and base one of the seven flat 2-orbifolds T,Kb,A,Mb,S(2,2,2,2),P(2,2) or D(2,2), and outline a classification of such 4-manifolds.
Unified framework for simple question answering using subgraph ranking and joint-scoring.
problem Simple question answering with knowledge graphs is challenging.
method Unified framework focusing on subgraph selection and fact selection, with novel ranking and joint-scoring methods.
result Achieved state-of-the-art accuracy of 85.44% on SimpleQuestions dataset.
Improves slot key and value prediction for unseen entities.
problem Dealing with unseen slot keys and values in real-world dialogue systems.
method Leverages external knowledge bases to project slots into an attribute space and generate candidate keys and values.
result Significant improvements in F1 score and accuracy (57.7% and 82.7%, respectively) over a previous approach.
mGENRE improves multilingual entity linking with autoregressive sequence prediction.
problem Multilingual Entity Linking (MEL) task of resolving language-specific mentions to a multilingual Knowledge Base.
method Autoregressive sequence-to-sequence system that cross-encodes mention strings and entity names.
result Over 50% improvement in average accuracy in zero-shot settings.
Training-free source selection for LLM families with shared vocabularies
problem Source selection for LLM families with shared vocabularies
method Fisher alignment at vocabulary scale
result Fisher alignment is a cosine between kernel mean embeddings in the joint activation-error space
A Kuranishi space is a topological space with a Kuranishi structure, defined by Fukaya and Ono. Kuranishi structures occur naturally on moduli spaces of J-holomorphic curves in symplectic geometry. This paper is a brief introduction to the author's book arXiv:0707.3572. Let Y be an orbifold and R a Q-algebra. We define…
Proposes a new method for conversational agents using deep learning.
problem Building coherent and non-monotonous conversational agents with proper discourse and coverage.
method End-to-end multi-stream deep learning architecture leveraging contextual and syntactic information.
result Significantly improved next sentence prediction task.
Generative compression technique reduces neural network size and improves performance on microcontrollers.
problem Memory constraints on microcontrollers limit the size of neural networks, especially for 1x1 pointwise (PW) mixers.
method HYPER-TINYPW uses a shared micro-MLP to generate PW kernels from tiny per-layer codes, reducing memory usage.
result HYPER-TINYPW achieves comparable performance to larger models while being significantly smaller (225 kB vs 1.4 MB).
Resource allocation improved using machine learning from terminal positions.
problem Optimizing resource allocation in next-gen wireless systems with fast-changing channel conditions.
method Supervised machine learning using position information of mobile terminals.
result Coordinates-based resource allocation performs similarly to traditional CSI-based methods.
Combines ML and KB modeling for large chaotic systems.
problem Predicting large, complex, spatiotemporal systems with limited data.
method Parallel ML prediction and hybrid approach combining ML and KB.
result Excellent performance and reduced training data needed.
FastGRNN improves RNN accuracy while drastically reducing model size.
problem Inaccurate training and inefficient prediction in RNNs.
method FastGRNN uses a residual connection and gate to achieve state-of-the-art accuracy with a much smaller model.
result FastGRNN achieves state-of-the-art accuracy with models up to 35x smaller than existing RNNs.
This paper shows that scientific discovery can be efficiently learned via compositional function trees, reducing the sample complexity.
problem Statistical and computational intractability of scientific discovery via symbolic regression.
method PAC learning approach focusing on compositional function trees built from a finite vocabulary of smooth operators.
result The Rademacher complexity and excess risk are controlled by depth and Lipschitz constants of the base operators, leading to finite-union bounds and high-probability risk bounds.
TinyBayes detects crop diseases from images on edge devices with high accuracy and minimal resources.
problem Automated disease detection for cocoa crops in resource-constrained settings.
method Combines YOLOv8-Nano for lesion localisation, MobileNetV3-Small for feature extraction, and Jacobi prior for Bayesian classification.
result Achieves 78.7% accuracy on Amini Cocoa Contamination Challenge dataset with 9.5 MB model size and 150 ms inference time.
The study examines conditions for completeness and simplicity in hom-Lie superalgebras.
problem Conditions for completeness and simplicity in hom-Lie superalgebras.
method Equivalent conditions and derivations analysis.
result Conditions for completeness and simplicity in hom-Lie superalgebras.
We prove that the supergravity r- and c-maps preserve completeness. As a consequence, any component H of a hypersurface {h=1} defined by a homogeneous cubic polynomial such that -d^2 h is a complete Riemannian metric on H defines a complete projective special Kahler manifold and any complete projective special Kahler m…
We give several applications of a lemma on completeness used by Osserman to show the meromorphicity of Weierstrass data for complete minimal surfaces with finite total curvature. Completeness and weak completeness are defined for several classes of surfaces which admit singular points. The completeness lemma is a usefu…
Study of knot group completions links Alexander polynomials.
problem Determining knot equivalence via group completions.
method Analyzing completed group rings and Alexander modules.
result Isomorphic knot group completions imply identical Alexander polynomials.
Simplifies matrix completion with statistical models.
problem Matrix completion under MCAR assumption.
method Statistical models and missing data analysis.
result Matrix completion valid without MCAR assumption.
New invariant defined for complete and bipartite graphs, determining Thurston-Bennequin numbers.
problem Determining Thurston-Bennequin numbers for complete and bipartite Legendrian graphs.
method Defined a total Thurston-Bennequin number, showed its determination by 3-cycles for complete graphs and 4-cycles for bipartite graphs.
result The total Thurston-Bennequin number is a new invariant that determines Thurston-Bennequin numbers for complete and bipartite graphs.
Completing segments of a real tree doesn't yield a complete space.
problem Completing segments of a real tree.
method Analyzing the field of real Puiseux series and the tree defined by Brumfiel.
result Completing all segments of the tree does not result in a complete metric space.
The paper classifies 2D complete λ-surfaces in 3D space.
problem Classifying complete λ-surfaces in R3. method Complete classification of 2D complete λ-surfaces with constant squared norm of the second fundamental form. result A complete classification for 2-dimensional complete λ-surfaces in Euclidean space R3 with constant squared norm of the second fundamental form. Study on geodesic completeness for Type A surfaces.
problem Determining geodesic completeness for Type A surfaces.
method Analyzing constant Christoffel symbols to determine geodesic completeness.
result A method to determine if a set of constant Christoffel symbols can model a complete surface.
Study geodesic and affine Killing completeness in homogeneous affine surfaces.
problem Geodesic and affine Killing completeness in homogeneous affine surfaces.
method Examined using the solution space of the quasi-Einstein equation.
result Characterized geodesic and affine Killing completeness in homogeneous affine surfaces.
Study directed completion of spacetimes, focusing on Schwarzschild spacetime.
problem Characterizing directed completions of spacetimes.
method Directed completion of Lorentzian pre-length spaces, focusing on Schwarzschild spacetime.
result Directed completion of Schwarzschild spacetime coincides with future causal completion.
Completeness of surface metrics established for Sobolev spaces.
problem Ensuring completeness of reparametrization-invariant Sobolev metrics on surface spaces.
method Recasting completeness criteria for infinite-dimensional Riemannian manifolds and applying geometric estimates based on the Michael--Simon--Sobolev inequality.
result Established metric and geodesic completeness for specific Sobolev metrics on immersed surfaces, validating Mumford's conjecture.
Geodesic completeness proven for all compact locally symmetric Lorentz manifolds.
problem Geodesic completeness of compact locally symmetric Lorentz manifolds.
method Proof in all remaining cases using completeness result.
result All compact, locally symmetric Lorentz manifolds are geodesically complete.
The study classifies complete Lagrangian self-shrinkers in 4D space.
problem Classifying complete Lagrangian self-shrinkers in 4D space.
method Complete classification of 2D complete Lagrangian self-shrinkers with constant squared norm of the second fundamental form.
result A complete classification for 2-dimensional complete Lagrangian self-shrinkers in R4 with constant squared norm of the second fundamental form. The paper classifies 3D complete gradient Yamabe solitons.
problem Classifying nontrivial 3D complete gradient Yamabe solitons.
method Analyzing properties of Yamabe solitons to show rotationally symmetry.
result Nontrivial non-flat 3D complete steady gradient Yamabe solitons are rotationally symmetric.
Incomplete markets are statistically indistinguishable from complete ones.
problem Statistical evaluation of market completeness under uncertainty.
method Investigation of discrete time stock market models, showing incompleteness is non-robust.
result Incomplete markets are statistically equivalent to complete ones.
Turing complete flow on 4-sphere preserves volume.
problem Creating a Turing complete flow on a 4-sphere.
method Smooth, conservative flow on the 4-sphere.
result Achieved a Turing complete, volume-preserving flow.
Study disproves conjecture about metric completion of curve spaces.
problem Completeness properties of spaces of immersed curves with reparametrization-invariant metrics.
method Examined Sobolev-type metrics on real-valued immersed curves, demonstrating multiple distinct limit points.
result Metric completion of spaces of immersed open curves includes multiple distinct limit points, not a single point as previously conjectured.
Low-rank matrix completion (LRMC) problems arise in a wide variety of applications. Previous theory mainly provides conditions for completion under missing-at-random samplings. This paper studies deterministic conditions for completion. An incomplete d×N matrix is finitely rank-r completable if there are at …
Survey of tensor completion algorithms for big data analytics.
problem Filling missing entries in tensors.
method Overview of recent tensor completion algorithms.
result Advances in tensor completion for big data.
Polyhedral semantics for intermediate logics; Nerve Criterion ensures completeness.
problem Characterize polyhedrally-complete intermediate logics.
method Developed Nerve Criterion to characterize polyhedrally-complete logics combinatorially.
result Nerve Criterion provides a necessary and sufficient condition for polyhedrally-completeness.