Ramji Venkataramanan

Name:	Ramji Venkataramanan
Affiliation:	University of Cambridge
E-mail:	(only provided to users who are logged into talks.cam)
Last login:	17 Apr 2026, 4:55 p.m.

Public lists managed by Ramji Venkataramanan

• Communications Research Group Seminar
• Information Engineering Distinguished Lecture Series
• Information Theory Seminar
• Machine learning
• Probabilistic Systems, Information, and Inference Group Seminars

Talks given by Ramji Venkataramanan

Obviously this only lists talks that are listed through talks.cam. Furthermore, this facility only works if the speaker's e-mail was specified in a talk. Most talks have not done this.

• Bayes-optimal estimation in generalized linear models
• Approximate Message Passing Algorithms
• Capacity-achieving codes for the AWGN channel via approximate message passing decoding
• Low-complexity codes for Compression and Communication via Sparse Regression

Talks organised by Ramji Venkataramanan

This list is based on what was entered into the 'organiser' field in a talk. It may not mean that Ramji Venkataramanan actually organised the talk, they may have been responsible only for entering the talk into the talks.cam system.

• A Unified Framework for Change of Measure Inequalities: Applications to Generalization, Memorization and Privacy
• Group Entropies: functionals on probability spaces, state space growth rates, energy, and connections to thermodynamics
• Towards a Theoretical Understanding of Deep Learning via the Minimum Description Length Principle
• The Minimum Description Length Principle and Machine Learning
• Information Constraints in Human Decision-Making: From Theory to Computation
• Statistical Investigations into the Unseen: Missing Mass for Markov Samples and Natural Distribution Estimation
• Variational Inference for Lévy Process-Driven SDEs via Neural Tilting
• Zero-Error Communications over Modulo-Additive Noise Channels with Assistance
• De Bruijn's identity and stability in the Entropy Power Inequality without finite variance
• Statistical Signal Processing for Quantum Error Mitigation
• Efficient gradient coding for mitigating stragglers within distributed machine learning
• Inequalities Revisited
• Inequalities Revisited
• Latent Concepts in Large Language Models
• Learning Privately in High Dimensions
• Cambridge Information Theory Colloquium
• Causal Representation Learning
• Graph Data Compression: Practical Methods and Information-Theoretic Limits
• Group Testing: Something old, something new, something borrowed
• Entropy comparison inequalities with applications to additive noise channels
• Data Compression with Relative Entropy Coding
• Can kernel machines be a viable alternative to deep neural networks?
• Sampling using Diffusion Processes
• Time-varying Signal Estimation Using Dynamic Topological Graphs
• Generalization and Informativeness of Conformal Prediction
• From Classical to Quantum: Uniform Continuity Bounds on Entropies in Infinite Dimensions
• A State-Space Perspective on Modelling and Inference for Online Skill Rating
• Symmetrized KL information: Channel Capacity and Learning Theory
• Structural, Temporal and Semantic Information
• Different Target Prediction Algorithms for Automotive, HRI and VR Digital Twin
• Communication over many-user channels via Approximate Message Passing
• Quickest Change Detection Using Mismatched CUSUM
• Information Theory Colloquium
• Some combinatorial problems in information theory
• Quantum Machine Learning: An Information-Theoretic Perspective
• Information-theoretic techniques and context-tree methods for time series
• A theory of social balance
• The Role of Information Measures on the Regularization of Empirical Risk Minimization
• Provably Safe Certification for Machine Learning Models under Adversarial Attacks
• Statistical-Computational Tradeoffs in Mixed Sparse Linear Regression
• A functional perspective on Information Measures
• AI for Sound
• AI for Sound
• Causal Identification: Are We There Yet?
• Approximate fixed points of classical and quantum channels and robustness theory of quantum Markov chains
• Fundamental limits in structured PCA, and how to reach them
• Generalization Bounds via Online Learning
• Discriminating Classical and Quantum Channels
• Semantic and Pragmatic Communications
• Bayes-optimal estimation in generalized linear models
• An Entropy-Based Model for Hierarchical Learning
• How the strength of the inductive bias affects the generalization performance of interpolators
• Communication in the presence of adversarial jamming: The curious case of the erasure channel
• Energy-Optimal Signaling using the Example of Optical Communication
• On the monotonicity of entropy in the discrete entropic central limit theorem
• Title to be confirmed
• Strong and epsilon-dependent converses for source or channel coding and for hypothesis testing
• Fundamental Limits of Learning with Feedforward and Recurrent Neural Networks
• Computational Imaging and Sensing: Theory and Applications
• A mathematical theory of deep neural networks
• Challenges and Opportunities in Computational Imaging and Sensing
• On the Stability and the Uniform Propagation of Chaos Properties of Ensemble Kalman-Bucy Filters
• Reliability function near the zero error capacity
• Lie Group Machine Learning and Natural Gradient from Information Geometry
• Gradient-based Adaptive Markov Chain Monte Carlo
• Random Caching Based Transmission in Ultra-Dense Wireless Networks
• Simple Reinforcement Learning Algorithms for Continuous State and Action Space Systems
• A local weak limit approach to the study of graphical data
• The Statistical Finite Element Method
• Deep Learning for Multifarious Speech Processing: Tackling Multiple Speakers, Microphones, and Languages
• Deep Learning for Multifarious Speech Processing: Tackling Multiple Speakers, Microphones, and Languages
• Can machine learning trump theory in communication system design?
• Symmetry, bifurcation, and multi-agent decision-making
• Deep Reinforcement Learning: from AlphaGo to AlphaStar
• Unleashing your inner maker
• Latent Variable Models for Bayesian Inference with Stable Distributions and Processes
• On optimal sampling in off-the-grid sparse regularisation.
• Estimating low-rank matrices via approximate message passing
• Fastest Convergence for Reinforcement Learning
• Design techniques for sparse regression codes
• Geometric MCMC for infinite-dimensional inverse problems
• Active Machine Learning: From Theory to Practice
• Information-theoretic perspectives on learning algorithms
• Measurement-dependent Noisy Search: An Information Acquisition Approach
• Biological Systems as Communication Networks
• Bilinear Inverse Problems: How much does structure help? (Leverhulme Lecture)
• Models and Capacity Bounds for Optical Fibre Channels
• High Resolution Optical and SAR Satellite Image Processing for Disaster Management using Hierarchical MRFs
• Tracking intentionality using behavioural models and Bayesian methods.
• Multi-band Image Super-resolution
• Algorithms and bounds for group testing
• Cluster-Seeking Shrinkage Estimators
• Exploiting Asymptotic Structure for Resolution Enhancement in Physical Imaging Systems
• Shrinkage Estimation in High Dimensions
• Adaptive Group Sparsity Using the Ordered Weighted l1 Regularizer
• Approximate Smoothing and Parameter Estimation in High-Dimensional State-Space Models
• Scalable inference for a full multivariate stochastic volatility model
• Ocean Heat and Hot air (with apologies to David MacKay)
• Cloud Radio Access Networks: Challenges and (Some) Solutions
• Gain from Multiple Measurements: Measurement Diversity and Resource Allocation
• Non-stationary Network Modelling by Particle Filtering: case of Gene Interaction Networks
• Capturing Accurate Colour Images
• Construction of Capacity-Achieving Lattice Codes: Polar Lattices
• A Novel Application of Information Theory in Heart Sound Signal Analysis for Cardiovascular Disease Diagnosis
• Characterizing degrees of freedom through additive combinatorics
• Eye Gaze Tracking
• Bayesian estimation for multi-object systems
• PREMIER: PRobabilistic Error-correction using Markov Inference in Errored Reads
• Online Robust Principal Components Analysis
• Factor Graph Transforms
• Multilevel sequential Monte Carlo Samplers.
• Recent Advances in Information Processing
• Inferring Cancer Evolution
• Using random linear network coding in dynamic storage environments
• Sequential Monte Carlo for graphical models: Graph decompositions and Divide-and-Conquer SMC
• The application of compressed sensing for longitudinal MRI
• Title to be confirmed
• Tracking the odd: Meter inference in musical audio using particle filters
• Compressible priors for high-dimensional statistics
• SCATTERING CONVOLUTION NETWORKS and DUAL-TREE WAVELETS
• On designing robust cost functions – applications to pattern analysis
• Title to be confirmed
• Radio Aspects of the Home Area Network for Smart Metering
• Dual-to-kernel learning with ideals
• Multiple Description Coding
• Wireless communication in electromagnetic cavities
• Classification on the Grassmann Manifold: Performance Limits of Compressive Classifiers
• Is the Gaussian distribution "Normal"?: Signal processing with alpha-stable distributions
• Joint Source-Channel Coding with Fading Channel and Side Information
• INDEPENDENT COMPONENT ANALYSIS VIA NONPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION
• Dynamic State Estimation using Dirac Mixture Approximation and Directional Statistics
• Communication by Statistical Regression
• Understanding Audio and Video at Google
• Bandlimited Intensity Modulation
• Estimation with Incomplete State Information in the Smart Grid
• Energy-efficient wireless communications
• Probabilistic modelling of time-frequency representations with application to music signals
• Interactive Codes for File Synchronization
• On the convergence of Adaptive sequential Monte Carlo Methods
• Demodulation and time-frequency analysis as inference
• Low-complexity codes for Compression and Communication via Sparse Regression
• High-SNR Asymptotics of Mutual Information for Discrete Constellations