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Description to be confirmed If you have a question about this list, please contact: dw304. If you have a question about a specific talk, click on that talk to find its organiser. 1 upcoming talk and 307 talks in the archive. Google's Approach to Building Relationships with Universities: Presentation and Talk by Dr David J Harper
Dendritic computation in pyramidal neurons.
Computational Neuroscience Journal Club
Matrix Concentration Inequalities via the Method of Exchangeable Pairs
Deep Gaussian Processes
Computational Neuroscience Journal Club
Approaches to statistical modeling of network data
Demixing scents: Sampling-based inference in olfaction.
Computational Neuroscience Journal Club
Bayesian nonparametric methods for non-exchangeable data
Non-parametric Bayesian Chromatin State Segmentation
Computational Neuroscience Journal Club
Fast Variational Inference in the Conjugate Exponential Family
University Lectureship in Computational Neuroscience candidate talks
Computational Neuroscience Journal Club
An application of HDP And IBP for stream-based action recognition and high dimensional data
Using Context and Insight for the Analysis of LittleData?
Feature allocations, probability functions, and paintboxes
Modelling Reciprocating Relationships with Hawkes Processes
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables
Computational Neuroscience Journal Club
Computational Neuroscience Course (4G3)4G3 course -- repeats Wednesdays at 12noon, Thursday at 2pm during Lent 2013
The combinatorial structure underlying a beta processes is that of a continuum of Blackwell-MacQueen urn schemes
Learning of Milky Way Model Parameters Using Matrix-variate Data in a New Gaussian Process-based Method
Computational Neuroscience Journal Club
Coding with Dendrites
Computational Neuroscience Journal Club
Space, sleep, brain rhythms and memory
Identification of causal effects
Probabilistic methods for biomolecular structure simulations
Computer Laboratory Systems Research Group Seminar Distributed, Real-Time Bayesian Learning in Online Services
Computational Neuroscience Journal Club
Compressed Sensing Applications in Functional Magnetic Resonance Imaging
Microsoft Research Cambridge, public talks Convergent and Scalable Algorithms for Expectation Propagation Approximate Bayesian InferenceThis event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Multi-Label Learning with Millions of Categories
Efficient Sampling with Kernel Herding
Perceiving is Believing: Bayesian inference in unexpected places.
Frank-Wolfe optimization insights in machine learning
Deep learning for vision: a case study for visual textures, and some thoughts on a general framework
Thermodynamics as a Theory of Decision-Making with Information Processing Costs
Human Behavior Classification with Infinite Hidden Conditional Random Fields
Fast Gaussian process learning for regression, semi-supervised classification, and multiway analysis
Non-parametric Bayesian Learning of User Preferences: Elicitation, Sparsification and Beyond
Structured Prediction using Linear Programming Relaxations
Computational Neuroscience Journal Club
Computational and Biological Learning Seminar Series Optimal integration of top-down and bottom-up uncertainty in humans, monkeys, and neural networks
Discovery of Complex Behaviors through Contact-Invariant Optimization
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Learning with nonparametric dependence and divergence estimation
Past work and future interests: respectively, the scattering of Anyons and Monte Carlo methods
Visuomotor behavior in naturalistic tasks: from receptive fields to value functions
Non-parametric Bayesian Method and Maximum-A-Posteriori Inference in Statistical Machine Translation
Computational and Biological Learning Seminar Series Optimal encoding and decoding in sensory populations
"Probing sensory representations with metameric stimuli"The host for this talk is Máté Lengyel, Engineering Department. Note that the title and topic of the talk have been revised.
Adrian Seminars in Neuroscience Near-optimal integration of evidence for decision-making in the rat.
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Infinite Structured Explicit Duration Hidden Markov Models
Probabilistic computing: computation as universal stochastic inference, not deterministic calculation
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Scaling Machine Learning for the Internet
Computational Neuroscience Journal Club
Bayesian Quadrature for Prediction and Optimisation
Modeling a non-linear EPSPs integration site in dendrites and its impact on computational capacities
Efficient MCMC for Continuous Time Discrete State Systems
A Maximum Entropy Perspective on Spectral Dimensionality Reduction
Computational Neuroscience Journal Club
Variational Inference for Non-Conjugate Models
Computational Neuroscience Journal Club
Not so naive Bayesian classification
Computational Neuroscience Journal Club
Bayesian Nonparametrics: Latent Feature and Prediction Models, and Efficient Inference
Machine Learning Markets
Computational Neuroscience Journal Club
Factored Shapes and Appearances for Parts-based Object Understanding AND Transformation Equivariant Boltzmann Machines
Reconciling intuitive and Newtonian physics
Optimal Reinforcement Learning for Gaussian Systems
Exclusive Pólya Urns and their applications
Computational Neuroscience Journal Club
Approximate Bayesian Inference for Large Scale Inverse Problems: A Computational Viewpoint
Some Practical Reflections on Graphical Models
Beyond Keyword Search: Discovering Relevant Scientific Literature
Graphical Models for Bandit Problems
Bayesian regression and classification with multivariate sparsifying priors
Organization of neuronal population activity in auditory cortex.
Computational Neuroscience Journal Club
An FX trading system using adaptive reinforcement learning(rescheduled from May 24th)
Censored Exploration in Dark Pools
Computational Neuroscience Journal Club
An FX trading system using adaptive reinforcement learningRESCHEDULED FOR JUNE 7th
Computational Neuroscience Journal Club
Navigational guidance systems in the human brainThe host for this talk is Dr. Máté Lengyel, Engineering Dept.
Characterization of the Ewens-Pitman family of random partitions by a deletion property and a de Finetti-type theorem for exchangeable hierarchies
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Nonlinear Dynamics of Learning
Exponential Conditional Volatility Models
Challenges in implementing the Bayesian paradigm
Expectation Propagation in Sparse Linear Models with Spike and Slab Priors
Probabilistic matrix factorization for reconstruction of missing data
Title to be confirmed
Conserved principles of movement generationThe host for this talk is Dr. Máté Lengyel, Engineering Dept., m.lengyel@eng.cam.ac.uk
Computational Neuroscience Journal Club
Differential Geometric MCMC Methods
Mining viral datasets
Computational Neuroscience Journal Club
Universal Bayesian Agents: Theory and Applications
Machine learning in cancer research (a.k.a CRI meets CUED)(note new date)
Novi Quadrianto
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Learning item trees for collaborative filtering with implicit feedback
Non-Smooth-Norm Image Reconstruction from Noisy Data
Crowdsourcing data modelling
CANCELLEDCANCELLED
Short talks: Mixed Cumulative Distribution Networks; Nonparametric Bayesian community discovery in social networks; Expectation Propagation for Dirichlet Process Mixture Models
Parallel dendritic processing and hippocampal spatial representations
How the brain makes decisionsTea and Cakes available in 2nd Floor Seminar Room from 4pm
Computational Neuroscience Course (4G3)4G3 course -- repeats Tues at 10am, Wed at 9am during Michaelmas
Computational Neuroscience Journal Club
Searching for Knowledge Instead of Web Pages
Optimality among optimals: decision making from neurobiological ‘noisy’ signals within the cortico-basal-ganglia system
Bayesian Inference with Kernels
Computational and Biological Learning Seminar Series Continuous control of brain computer interfaces based on a covert spatial attention paradigm
Translational biomedical informatics research in a clinical neurosurgery environment
On the Equivalence of Graph Cuts and Max-product Belief Propagation
Culture wars, voting and polarization: divisions and unities in modern American politicsgeneral audience talk (non-technical) -- NOTE change of room to LR4!
Creating structured and flexible models: some open problems
Efficient Bayesian analysis of multiple changepoint models
Learning Common Grammar from Multilingual Corpus / Online Multiscale Dynamic Topic Models
Scalable Parallel Computing with CUDA
Using transformed domains to sparsify Gaussian Processes
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Natural Conjugate Gradient Learning for Fixed-Form Variational Bayes
Sparse Factor Analysis Applied to Three Biological Problems
Using topic models to help cure cancer
Message Passing In Centralized Databaseshort talk
Structured Prediction Cascades
Parametric Bandits, Query Learning, and the Haystack Dimension
Learning predictive models for visual motion extrapolation
From tuning curves to behaviour
Computational Neuroscience Journal Club
Mapping affective decisions in depression using reinforcement learning tools
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Slice sampling with latent Gaussian models
Dynamic Network Tomography: Model, Algorithm, Theory, and Application
Making Sense of Data - A Research Agenda
Recursive CRFs for Scalable Visionshort talk
Computational and Biological Learning Seminar Series Title to be confirmedshort talk
Subspace Codes for Adversarial Error-Correction in Network Codingshort talk
Computational and Biological Learning Seminar Series Title to be confirmedShort talk
Computational Neuroscience Journal Club
Bayesian Inference in Networks of Queues
Stochastic Outlier Selection
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Mind Reading by Machine Learning: Optimal Experimental DesignShort talk
Computational Neuroscience Journal Club
Machine Learning Course (4F13)4F13 course - repeats Wed, Thurs at 10am during Lent
CANCELLED: Learning Components for Human SensingCANCELLED
Visuospatial ReasoningShort Talk
Machine Learning Course (4F13)4F13 course - repeats Wed, Thurs at 10am during Lent
Computational Neuroscience Journal Club
Optimal Tag Sets for Automatic Image Annotationshort talk
Joint imputation and estimation of haplotype transition probabilities
Computational Neuroscience Journal Club
Indian Buffet Processes with Power-law Behaviour
Gaussian Processes for Active Data Selection, Faults, Changepoints and Sensor Selection
Computational Neuroscience Journal Club
KL control theory and decision making under uncertainty
Computational Neuroscience Journal Club
Adrian Seminars in Neuroscience “Modeling synaptic plasticity across multiple time scales”.
Information theoretic model selection in clustering
Computational Neuroscience Journal Club
Motor Skills Learning for Robotics
Computational Neuroscience Journal Club
Reduced cortical neuron models: Experiment and theory
Coconut: Optimizing computations for machine learning
Computational Neuroscience Journal Club
Capacity of Spiking Neural Networks
CANCELLEDCancelled
Convex Variational Bayesian Inference for Large Scale Generalized Linear Models
Computable Probability Theory
Computational Neuroscience Journal Club
Is the homunculus `aware' of sensory adaptation?
Computational Neuroscience Journal Club
Using gradient descent for optimization and learning
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Computational and Biological Learning Seminar Series Algorithms for Understanding Motor Cortical Processing and Neural Prosthetic Systems
Coding with envelopes, receptive fields and plasticity
Learning from Measurements in Exponential Families
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Shrinkage regression for multivariate inference with missing data, with an application to portfolio balancing
Quasi-linear Sensor Management
An Introduction to TranscriptomicsMachine Learning Tutorial Lecture
Computational Neuroscience Journal Club
Computational and Biological Learning Seminar Series Mind reading by machine learning: an ideal observer based analysis of cognitive scientific experiments
Generalization in Learning
Stochastic control as an inference problem
Computational Neuroscience Journal Club
Extending the Affinity Propagation Model
Computational Neuroscience Journal Club
The Block Diagonal Infinite Hidden Markov Model
Probabilistic Graph Models for Debugging Software
Computational Neuroscience Journal Club
HMMs for Protein Sequencing from Mass Spectrometry Data
Deep Networks for VisionMachine Learning Tutorial Lecture
Computational Neuroscience Journal Club
Consensus finding, exponential models and infinite rankings
Computational Neuroscience Journal Club
Computational Neuroscience Journal Club
Foundations of Nonparametric Bayesian Methods (Part III)
Efficient Sequential Monte Carlo Inference for Kingman's CoalescentNote unusual time
Context in human robot interaction
Foundations of Nonparametric Bayesian Methods (Part II)
Computational Neuroscience Journal Club
Foundations of Nonparametric Bayesian Methods (Part I)
Shared Segmentation of Natural Scenes using Dependent Pitman-Yor Processes
Signal Processing and Communications Laboratory Seminars From calcium imaging to spikes, using sequential Monte Carlo methods
Computational Neuroscience Journal Club
Spoken Dialogue Management
A Bayesian approach to language learning
Learning Bigrams from Unigrams
Nonparametric Bayesian Natural Language Model Domain Adaptation: A Hierarchical, Hierarchical Pitman-Yor Process Language Model
Computational Neuroscience Journal Club
Bayesian approaches to autonomous Bayesian real-time learning
Non-negative matrix factorization with Gaussian process priors
Matrix Factorization and Relational Learning
Assessing the effects of statistical dependencies on neural population coding in the visual pathway
Double Feature: Optimal Precoding for MIMO and Divergence Estimation for Continuous Distributions
Nonparametric Bayesian Learning of Switching Dynamical Systems
Message-passing inference on graphical models
Bayesian analysis of complex biological systems
Variational inference for partially observed diffusion processes
Computational and Biological Learning Seminar Series Seeing Patterns in Randomness: Irrational Superstition or Adaptive Behavior?
Assessing high-dimensional latent variable models
Identification of dynamical subpopulations, optimal experiment design and more
H-Infinity Clustering
Sustainable Energy - without the hot air
Modeling Behaviour in Economic Games using Game-Theoretic POMDPs
Talking with Robots: A Case Study in Architectures for Cognitive Robotics
An Introduction to Statistical Learning TheoryMachine Learning Tutorial Lecture
Beam Sampling for Infinite Hidden Markov Models
Learning quantum physics
Convergence analysis of the EM algorithm and joint minimization of free energy
Discriminative Methods with Structure
A Bayesian approach to network modularity: inferring the structure and scale of modular networks
Inductive Logic ProgrammingMachine Learning Tutorial Lecture
Statistical Machine TranslationMachine Learning Tutorial Lecture
Model selection and model order adaptation for clustering
Expectation Propagation, Experimental Design for the Sparse Linear Model
Biomedical Image Search
Information RetrievalMachine Learning Tutorial Lecture
Stable distribution and data sketching
Reinforcement LearningMachine Learning Tutorial Lecture (Note unusual day)
Modeling Science: Topic models of Scientific Journals and Other Large Document Collections
Sparse Gaussian Process in Disease Mapping
Graphical ModelsMachine Learning Tutorial Lecture
Gene Regulatory Network Inference: A Kernel-Based Learning Approach
Error Correcting CodesMachine Learning Tutorial Lecture
Clinical data based optimal STI strategies for HIV: a reinforcement learning approach
Machine Learning Applications / Challenges in Natural Language ParsingMachine Learning Tutorial Lecture
An overview of covariance operators in Hilbert space, and their applications
Optimal Control and Reinforcement Learning with Gaussian Process Models
Prequential StatisticsMachine Learning Tutorial Lecture
Spectral ClusteringMachine Learning Tutorial Lecture
Group Theory and Machine LearningMachine Learning Tutorial Lecture
Hidden Common Cause Relations in Relational Learning
Optimal Spreading Sequences for Chaos-Based Communication Systems; Using CSK as a Case Study
Graph Kernels for Data Mining
Geometric Algorithms for Linear Independent Component Analysis
Covariate Shift Adaptation: Supervised Learning When Training and Test Inputs Have Different Distributions
Computational and Biological Learning Seminar Series A new mathematical framework for optimal choice of actions
Bayesian RankingAdvanced Machine Learning Tutorial Lecture
Logistic Regression with a Laplacian prior on the Eigenvalues: Convex duality and application to EEG classificationNote different room and time
Dirichlet Processes and Hierarchical Dirichlet ProcessesAdvanced Machine Learning Tutorial Lecture
An Introduction to Non-parametric Bayesian MethodsRoom changed this week!
Robot Localisation and MappingAdvanced Machine Learning Tutorial Lecture
Advanced MCMC MethodsAdvanced Machine Learning Tutorial Lecture
Expectation PropagationAdvanced Machine Learning Tutorial Lecture
CausalityAdvanced Tutorial Lecture Series on Machine Learning
Gaussian Processes for Machine LearningAdvanced Machine Learning Tutorial Lecture
Mixture Models and the EM AlgorithmAdvanced Machine Learning Tutorial Lecture
Probabilistic Dimensional Reduction with the Gaussian Process Latent Variable Model
Please see above for contact details for this list. |
Other lists11th Cambridge Immunology Forum 23.9.10 Health and Welfare Reading Group Experimental PsychologyOther talksQuantum Tunnelling Splittings in Water Clusters, from Ring-Polymer Instanton Theory Serre weights and de Rham cohomology of Shimura curves "Renal Cancer and Oxygen Sensing" Dendritic cell subsets in Th2 immunity Self-avoiding walk on regular graphs On a well-tempered diffusion |
David Barrett (ENS Paris).
Friday 24 May 2013, 09:30-10:30