Learning structured prediction models: a large margin approach

No abstract is available for this paper.

• Publication year

  2005

• Venue

  International Conference on Machine Learning

• Publication date

  2005-08-07

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1145/1102351.1102464
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Pattern Classification

  2012cited by this paper
• Learning structured prediction models : a large margin approach

  2005cited by this paper
• Support vector machine learning for interdependent and structured output spaces

  2004cited by this paper
• Learning associative Markov networks

  2004influential reference
• Large-Scale Prediction of Disulphide Bond Connectivity

  2004influential reference
• Inverse Combinatorial Optimization: A Survey on Problems, Methods, and Results

  2004cited by this paper
• Max-Margin Parsing

  2004cited by this paper
• Disulfide connectivity prediction using recursive neural networks and evolutionary information

  2004influential reference
• Hidden Markov Support Vector Machines

  2003influential reference
• Combinatorial optimization. Polyhedra and efficiency.

  2003influential reference
• Max-Margin Markov Networks

  2003cited by this paper
• Shape Matching and Object Recognition Using Shape Contexts

  2002cited by this paper
• Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms

  2002influential reference
• Prediction of disulfide connectivity in proteins

  2001cited by this paper
• Pattern classification, 2nd Edition

  2000cited by this paper
• Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

  1997cited by this paper
• Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features

  1983influential reference
• Pattern Classification

  1973cited by this paper
• Maximum matching and a polyhedron with 0,1-vertices

  1965influential reference
• Electronic Reprint Biological Crystallography the Protein Data Bank Biological Crystallography the Protein Data Bank

  year unknowncited by this paper

• D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems

  2026cites this paper
• Beyond Single-GPU: Scaling PDLP to Distributed Multi-GPU Systems

  2026cites this paper
• Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity

  2026cites this paper
• Inverse Optimization Without Inverse Optimization: Direct Solution Prediction with Transformer Models

  2026cites this paper
• Zeroth-order Proximal Clipped Gradient Method with Shifts for Distributed Stochastic Composite Optimization Problems with Infinite Variance

  2025cites this paper
• Gradient-free algorithms based on weight-balancing for online distributed optimisation

  2025cites this paper
• Efficient Inverse Multiagent Learning

  2025cites this paper
• Communication-Efficient Zeroth-Order Adaptive Optimization for Federated Learning

  2024cites this paper
• Zero Order Algorithm for Decentralized Optimization Problems

  2024cites this paper
• Deep Submodular Peripteral Networks

  2024cites this paper
• An Inexact Preconditioned Zeroth-Order Proximal Method for Composite Optimization

  2024cites this paper
• Is there Gender Bias in Dependency Parsing? Revisiting “Women’s Syntactic Resilience”

  2024cites this paper
• New aspects of black box conditional gradient: Variance reduction and one point feedback

  2024cites this paper
• Federated Learning Based Sparse Coding for Non-Intrusive Load Monitoring

  2024cites this paper
• Compositional Models for Estimating Causal Effects

  2024cites this paper
• Forgetting-Factor Regrets for Online Convex Optimization

  2024cites this paper
• Sparse Coding-Based Transfer Learning for Energy Disaggregation

  2024cites this paper
• Learning in Inverse Optimization: Incenter Cost, Augmented Suboptimality Loss, and Algorithms

  2023cites this paper
• Polynomial-Time Constrained Message Passing for Exact MAP Inference on Discrete Models with Global Dependencies

  2023cites this paper
• Inverse Reinforcement Learning Framework for Transferring Task Sequencing Policies from Humans to Robots in Manufacturing Applications

  2023cites this paper
• A tree-like structured perceptron for transition-based biomedical event extraction

  2023cites this paper
• A Graph Matching Approach to Tracking Neurons in Freely-Moving C. elegans

  2023cites this paper
• DAG Learning on the Permutahedron

  2023cites this paper
• SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres

  2023cites this paper
• Towards intelligent policy analysis: A discourse structure parsing technique for Chinese government document

  2023cites this paper
• Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey

  2023cites this paper
• Information Extraction in Low-Resource Scenarios: Survey and Perspective

  2022cites this paper
• Gradient‐free algorithms for distributed online convex optimization

  2022cites this paper
• Nested Named Entity Recognition as Corpus Aware Holistic Structure Parsing

  2022cites this paper
• Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations

  2022cites this paper
• Predictive Inference with Weak Supervision

  2022cites this paper
• A Character-Level Span-Based Model for Mandarin Prosodic Structure Prediction

  2022cites this paper
• Nested Named Entity Recognition as Holistic Structure Parsing

  2022cites this paper
• Learning to Approximate Industrial Problems by Operations Research Classic Problems

  2021cites this paper
• Scalable Projection-Free Optimization

  2021cites this paper
• VISIOCITY: A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization

  2021cites this paper
• Contextual Inverse Optimization: Offline and Online Learning

  2021influential citation
• Comparing Inverse Optimization and Machine Learning Methods for Imputing a Convex Objective Function

  2021cites this paper
• Fast automatic step size selection for zeroth-order nonconvex stochastic optimization

  2021cites this paper
• One-point feedback for composite optimization with applications to distributed and federated learning

  2021cites this paper
• Learning Syntax from Naturally-Occurring Bracketings

  2021cites this paper
• How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization

  2021cites this paper
• Learning to Match Mathematical Statements with Proofs

  2021influential citation
• On the Effectiveness of Richardson Extrapolation in Data Science

  2021cites this paper
• Aligning artificial intelligence with human values: reflections from a phenomenological perspective

  2021cites this paper
• On the parameter learning for Perturb-and-MAP models

  2021cites this paper
• Headed-Span-Based Projective Dependency Parsing

  2021cites this paper
• Combining (Second-Order) Graph-Based and Headed-Span-Based Projective Dependency Parsing

  2021cites this paper
• USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems

  2021cites this paper
• Inverse Optimization: Theory and Applications

  2021cites this paper
• In-Order Chart-Based Constituent Parsing

  2021cites this paper
• Structured Neural Models and Structured Decoding for Natural Language Processing

  2020influential citation
• LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction

  2020influential citation
• On the Effectiveness of Richardson Extrapolation in Machine Learning

  2020cites this paper
• Semi-supervised Autoencoding Projective Dependency Parsing

  2020cites this paper
• A Music Classification model based on metric learning applied to MP3 audio files

  2020cites this paper
• A Joint Deep Contextualized Word Representation for Deep Biaffine Dependency Parsing

  2020cites this paper
• Learning with Differentiable Perturbed Optimizers

  2020cites this paper
• Fast and Accurate Non-Projective Dependency Tree Linearization

  2020cites this paper
• From inverse optimal control to inverse reinforcement learning: A historical review

  2020cites this paper
• Consistent Structured Prediction with Max-Min Margin Markov Networks

  2020cites this paper
• Semi-supervised Parsing with a Variational Autoencoding Parser

  2020cites this paper
• A Simple Global Neural Discourse Parser

  2020cites this paper
• Learning Convex Optimization Models

  2020cites this paper
• Learning Linear Programs from Optimal Decisions

  2020cites this paper
• Adversarial Learning for 3D Matching

  2020cites this paper
• Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control

  2020cites this paper
• Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling

  2020cites this paper
• A contribution to Optimal Transport on incomparable spaces

  2020cites this paper
• Span-based Discontinuous Constituency Parsing: A Family of Exact Chart-based Algorithms with Time Complexities from O(nˆ6) Down to O(nˆ3)

  2020cites this paper
• Conditional Random Fields Based on Weighted Feature Difference Potential for Remote Sensing Image Classification

  2020cites this paper
• Polynomial-Time Exact MAP Inference on Discrete Models with Global Dependencies

  2019cites this paper
• Learning Explicit and Implicit Structures for Targeted Sentiment Analysis

  2019influential citation
• Learning Explicit and Implicit Structures for Targeted Sentiment Analysis

  2019influential citation
• Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions

  2019cites this paper
• Active Learning in Video Tracking

  2019cites this paper
• Learning with Fenchel-Young Losses

  2019influential citation
• The Differentiable Cross-Entropy Method

  2019cites this paper
• A General-Purpose Algorithm for Constrained Sequential Inference

  2019cites this paper
• Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification

  2019cites this paper
• Computational Linguistics: 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Hanoi, Vietnam, October 11–13, 2019, Revised Selected Papers

  2019cites this paper
• On Parameter Learning for Perturb-and-MAP Models. (Sur l'apprentissage des paramètres pour les modèles Perturb-and-MAP)

  2019cites this paper
• A Music Classification Model based on Metric Learning and Feature Extraction from MP3 Audio Files

  2019cites this paper
• Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization

  2019cites this paper
• Effective Approach to Joint Training of POS Tagging and Dependency Parsing Models

  2019cites this paper
• Supervised Training on Synthetic Languages: A Novel Framework for Unsupervised Parsing

  2019cites this paper
• Learning Explicit and Implicit Structures for Targeted Sentiment Analysis

  2019influential citation
• TDN: An Integrated Representation Learning Model of Knowledge Graphs

  2019cites this paper
• Risk-Sensitive Variational Bayes: Formulations and Bounds

  2019cites this paper
• Edge-Labeling Graph Neural Network for Few-Shot Learning

  2019cites this paper
• On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making

  2019cites this paper
• Learning Novelty-Aware Ranking of Answers to Complex Questions

  2019cites this paper
• Injecting spatial priors in Earth observation with machine vision

  2019cites this paper
• Parametric Majorization for Data-Driven Energy Minimization Methods

  2019cites this paper
• Learning Neural Sequence-to-Sequence Models from Weak Feedback with Bipolar Ramp Loss

  2019cites this paper
• The Interplay Between Loss Functions and Structural Constraints in Dependency Parsing

  2019cites this paper
• A Sequential Set Generation Method for Predicting Set-Valued Outputs

  2019cites this paper
• Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction

  2019cites this paper
• Efficient graph construction for similarity search on high dimensional data

  2019cites this paper
• Auto-Summarization: A Step Towards Unsupervised Learning of a Submodular Mixture

  2019cites this paper