Proceedings of the 29th International Conference on Machine Learning (ICML-12)

Abstract

This is an index to the papers that appear in the Proceedings of the 29th International Conference on Machine Learning (ICML-12). The conference was held in Edinburgh, Scotland, June 27th - July 3rd, 2012.

arXiv commentProceedings of the 29th International Conference on Machine Learning (ICML-12). Editors: John Langford and Joelle Pineau. Publisher: Omnipress, 2012

Cited by in corpus (126)

• Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation
• Brain Tumor Segmentation with Deep Neural Networks
• Graph Embedding Techniques, Applications, and Performance: A Survey
• Quantum machine learning in feature Hilbert spaces
• Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge
• Deep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Data
• Uncertainty Quantification in Scientific Machine Learning: Methods, Metrics, and Comparisons
• Physics-Informed Neural Networks for Multiphysics Data Assimilation with Application to Subsurface Transport
• Bayesian Consensus Clustering
• Layer-Wise Relevance Propagation for Explaining Deep Neural Network Decisions in MRI-Based Alzheimer's Disease Classification
• Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
• A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data
• Continuous-Time Gaussian Process Motion Planning via Probabilistic Inference
• Quantum Entanglement in Deep Learning Architectures
• Automated data processing and feature engineering for deep learning and big data applications: a survey
• Supporting Very Large Models using Automatic Dataflow Graph Partitioning
• Stochastic data-driven model predictive control using Gaussian processes
• Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks
• Feature Concatenation Multi-view Subspace Clustering
• Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines
• On the Random Batch Method for second order interacting particle systems
• Learning the PE Header, Malware Detection with Minimal Domain Knowledge
• Deep Learning for Logo Recognition
• Word-Entity Duet Representations for Document Ranking
• Friend, Collaborator, Student, Manager: How Design of an AI-Driven Game Level Editor Affects Creators
• $k$-POD: A Method for $k$-Means Clustering of Missing Data
• How priors of initial hyperparameters affect Gaussian process regression models
• Cellular automata as convolutional neural networks
• Convex Biclustering
• Quenches near Ising quantum criticality as a challenge for artificial neural networks
• Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks
• Deep Divergence-Based Approach to Clustering
• One Detector to Rule Them All: Towards a General Deepfake Attack Detection Framework
• 3D Bayesian Variational Full Waveform Inversion
• Low-rank plus sparse decomposition for exoplanet detection in direct-imaging ADI sequences. The LLSG algorithm
• Machine learning for transient discovery in Pan-STARRS1 difference imaging
• Sparse Convex Clustering
• A Diffusion model for POI recommendation
• Using Recurrent Neural Networks to Optimize Dynamical Decoupling for Quantum Memory
• A Similarity Measure for Material Appearance
• Deep Learning in Business Analytics: A Clash of Expectations and Reality
• Active emulation of computer codes with Gaussian processes -- Application to remote sensing
• Dual Space Graph Contrastive Learning
• Strong error analysis for stochastic gradient descent optimization algorithms
• Fast, Robust and Non-convex Subspace Recovery
• Deep learning for plasma tomography using the bolometer system at JET
• Combining pretrained CNN feature extractors to enhance clustering of complex natural images
• Point Processes with Gaussian Boson Sampling
• Are we done with object recognition? The iCub robot's perspective
• Convolutional Sparse Kernel Network for Unsupervised Medical Image Analysis
• Forging new worlds: high-resolution synthetic galaxies with chained generative adversarial networks
• Multimedia Semantic Integrity Assessment Using Joint Embedding Of Images And Text
• A Survey on the Densest Subgraph Problem and Its Variants
• Learning stable and predictive structures in kinetic systems: Benefits of a causal approach
• A Projector Quantum Monte Carlo Method for non-linear wavefunctions
• U(1) symmetric recurrent neural networks for quantum state reconstruction
• PDNet: Semantic Segmentation integrated with a Primal-Dual Network for Document binarization
• Low-Resource Text Classification using Domain-Adversarial Learning
• Learning Maximum Entropy Models from finite size datasets: a fast Data-Driven algorithm allows sampling from the posterior distribution
• Robust Subspace Clustering via Tighter Rank Approximation
• MultiScale Probability Map guided Index Pooling with Attention-based learning for Road and Building Segmentation
• Variable Selection and Task Grouping for Multi-Task Learning
• SMC Faster R-CNN: Toward a scene-specialized multi-object detector
• Operator Norm Inequalities between Tensor Unfoldings on the Partition Lattice
• Learning with hidden variables
• VN Network: Embedding Newly Emerging Entities with Virtual Neighbors
• Neural Parametric Fokker-Planck Equations
• On the role of synaptic stochasticity in training low-precision neural networks
• A Proximal Approach for a Class of Matrix Optimization Problems
• Jensen-Shannon Divergence Based Novel Loss Functions for Bayesian Neural Networks
• Coordination Event Detection and Initiator Identification in Time Series Data
• On Fair Selection in the Presence of Implicit and Differential Variance
• NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access
• Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification
• A Retrieve-and-Read Framework for Knowledge Graph Link Prediction
• Neural Discourse Relation Recognition with Semantic Memory
• Relational hyperevent models for the coevolution of coauthoring and citation networks
• PDP: Physics-Based Character Animation via Diffusion Policy
• On the Nyström and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets
• Infinite-dimensional Bayesian filtering for detection of quasi-periodic phenomena in spatio-temporal data
• Matrix Completion under Interval Uncertainty
• Physics-informed Tensor-train ConvLSTM for Volumetric Velocity Forecasting of Loop Current
• On the Effects of Low-Quality Training Data on Information Extraction from Clinical Reports
• Scalable Greedy Algorithms for Transfer Learning
• A Co-training Approach for Noisy Time Series Learning
• Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation
• Wide flat minima and optimal generalization in classifying high-dimensional Gaussian mixtures
• Sampling scheme for neuromorphic simulation of entangled quantum systems
• Modeling Dual Period-Varying Preferences for Takeaway Recommendation
• Robustness Analysis of Preconditioned Successive Projection Algorithm for General Form of Separable NMF Problem
• Learning to Rank Using Localized Geometric Mean Metrics
• Continuous Time Graph Processes with Known ERGM Equilibria: Contextual Review, Extensions, and Synthesis
• Diffuse-CLoC: Guided Diffusion for Physics-based Character Look-ahead Control
• Deep Learning Approach for Matrix Completion Using Manifold Learning
• Injection Optimization at Particle Accelerators via Reinforcement Learning: From Simulation to Real-World Application
• Data Poisoning Attacks to Locally Differentially Private Frequent Itemset Mining Protocols
• Random active path model of deep neural networks with diluted binary synapses
• Exact Gauss-Newton Optimization for Training Deep Neural Networks
• Physiological Gaussian Process Priors for the Hemodynamics in fMRI Analysis
• Single- to multi-fidelity history-dependent learning with uncertainty quantification and disentanglement: application to data-driven constitutive modeling
• Neural Network Approach to Scaling Analysis of Critical Phenomena
• Linear processes in high-dimension: phase space and critical properties
• Training Recurrent Neural Networks via Dynamical Trajectory-Based Optimization
• AdapMTL: Adaptive Pruning Framework for Multitask Learning Model
• Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation
• An adaptive Hessian approximated stochastic gradient MCMC method
• Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models
• Semi-supervised Vector-valued Learning: Improved Bounds and Algorithms
• Generalized Dirichlet-process-means for $f$-separable distortion measures
• Benchmarking the Fairness of Image Upsampling Methods
• Resilient Linear Classification: An Approach to Deal with Attacks on Training Data
• Refinement of Hottopixx Method for Nonnegative Matrix Factorization Under Noisy Separability
• DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach
• Limits on Inferring the Past
• A Bayesian Neural Network Approach for Tropospheric Temperature Retrievals from a Lidar Instrument
• Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs
• Towards Safe Synthetic Image Generation On the Web: A Multimodal Robust NSFW Defense and Million Scale Dataset
• Learning-Based Design of Off-Policy Gaussian Controllers: Integrating Model Predictive Control and Gaussian Process Regression
• Regularized Unconstrained Weakly Submodular Maximization
• Benchmarking Recommendation, Classification, and Tracing Based on Hugging Face Knowledge Graph
• Real-Time Cleaning and Refinement of Facial Animation Signals
• ReFrame: Rectification Framework for Image Explaining Architectures
• Rethinking Breiman's Dilemma in Neural Networks: Phase Transitions of Margin Dynamics
• Exploring Apprenticeship Learning for Player Modelling in Interactive Narratives
• Reinforcement Learning with Partial Parametric Model Knowledge
• Towards Designing Social Interventions For Online Climate Change Denialism Discussions