Monday

GeorgeAbeJackEvaCory
Coding 1


Distributed and Federated Learning (Inv)


Array Sensing (Inv)


Machine Learning and Logic (Inv)


Sequential Decision Making (Inv)


10:30 AMLow-complexity posterior matching over the binary symmetric channel with feedback

Richard Wesel

Federated representation learning through clustering

Erdem Koyuncu

Convergence Analysis of Robust and Sparse M-Estimation of DOA

Christoph Mecklenbrauker

Neuro-Symbolic Motivations for Logical Information Theory

Alexander Gray

Sequential conformal prediction for time series

Yao Xie

10:50 AMDeep Learning-based Error Correction Codes for Feedback Channels

Alberto Perotti

Analog-digital Scheduling for Federated Learning: A Communication-Efficient Approach

Nicolo Michelusi

A new radio to overcome critical link budgets

Ralf Müller

Towards a Unification of Logic and Information Theory

Luis Lastras

Federated Linear Contextual Bandits with User-level Differential Privacy

Jing Yang

11:10 AMOn graph codes for high-dimensional QKD

Lara Dolecek

Distributed learning in networks with delays

Hamid Jafarkhani

Direction of Arrival refinement using Wirtinger gradients

Peter Gerstoft

Fat Shattering, Joint Measurability, and PAC Learnability of Quantum Hypothesis Classes

Abram Magner

Fixed-Budget Differentially Private Best Arm Identification

Vincent Tan

11:30 AMLow-Latency Decoding of Hypergraph-Product Codes

Bane Vasic

Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning

Suhas Diggavi

Array-informed waveform design and the role of redundancy

Piya Pal

Oracle-Efficient Hybrid Online Learning with Unknown Distribution

Changlong Wu

Best arm identification for prompt learning under a limited budget

Cong Shen

Quantum LDPC Codes for Fault-Tolerant Computation (Inv)


Distributed Learning and Optimization


Lloyd Welch: In Memoriam (Inv)


Statistical learning for analysis and design of control systems (Inv)


Info Theory and Wireless


1:20 PMSpatially-Coupled QLDPC Codes

Siyi Yang

DIGEST: Fast and Communication Efficient Decentralized Learning with Local Updates

Hulya Seferoglu

On the Contributions of Lloyd Welch

P Vijay Kumar

Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss

Ingvar Ziemann

A Context-Aware CEO Problem

Daewon Seo

1:40 PMFault-Tolerant Quantum Computing with Quantum LDPC Codes

Narayanan Rengaswamy

Information aggregation and distributed learning in privacy-critical environments

Amin Rahimian

Lloyd Welch and the long life of Reed-Muller codes

Stephen Wicker

Toward Trustworthy Reinforcement Learning

Lin Yang

Instance-optimality in universal prediction

Alankrita Bhatt

2:00 PMConcatenated QLDPC Codes and Decoders

Nithin Raveendran

AltGDmin-based Fast and Federated Few-Shot Representation Learning

Namrata Vaswani

The Baum-Welch algorithm

Al Hales

Some Dynamics and Control Perspectives on Policy Gradient Methods

Sean Gao

title: Bridging the gap between electromagnetics and array processing

Robert Heath

2:20 PMBelief Propagation Decoding of Quantum LDPC Codes with Guided Decimation

Hanwen Yao

Learning for controls: scalable and adaptable safe controllers

Sylvia Herbert

ML Approaches to Info Theory (Inv)


Machine Learning and Control


Wireless Communications


Adversarial Robustness


Coding 2


3:00 PMNeural Compression with Latice Transform Coding

Shirin Saeedi Bidokhti

Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data

Nikolai Matni

Golden Modulation: a New and Effective Waveform for Massive IoT

Michele Zorzi

A communication-theoretic foundation for robust deep learning?

Upamanyu Madhow

Nested Lattice Codes Which Are Cyclic Groups

Brian Kurkoski

3:20 PMIn-Context Estimation using Transformers for Wireless Communications

Krishna Narayanan

Distributionally Robust Infinite Horizon Control

Babak Hassibi

Matrix Fractional Programming for Integrated Sensing and Communications

Wei Yu

Adversarially Robust Learning with Uncertain Perturbation Sets

Vinayak Pathak

Improved Belief Propagation Decoding of Polar Codes on Permuted Factor Graphs

Hiroshi Kamabe

3:40 PMMachine Learning-Aided Channel Coding

Hessam Mahdavifar

Wireless Video Streaming with Delayed Client-Feedback: A Constrained Decentralized Team View

Vijay Subramanian

OTFS 2.0 (Zak-OTFS) modulation: Near-optimal detection

Ananthanarayanan Chockalingam

Low-rank approximation and robustness

Vagelis Papalexakis

Simplified Successive Cancellation List Decoding of PAC Codes

Hamid Saber

4:00 PMData Driven Approach for Estimating and Achieving Capacity

Haim Permuter

The Surprising Power of Denoising

Peyman Milanfar

Human-Centered IoT Systems for Privacy and Health

Wei Sun

A Goldilocks Cost Constraint

Aaron Wagner

Tuesday

GeorgeAbeJackEvaCory
Coding


Info Theory 1


Topics and advances in sequential decision making (Inv)


Machine Learning


Complexity, Causality and Sequences


10:30 AMEnhancing the Error-Floor Performance of LDPC Codes: A Machine Learning Approach

Heeyoul Kwak

Zak-OTFS implementation using time and frequency windowing

Swaroop Gopalam

Towards instance optimal rates in learning from dependent data

Stephen Tu

Theoretical Guarantees of Data Augmented Last Layer Retraining Methods

Lalitha Sankar

Pi-Squared: Zero Knowledge Proofs of Mathematical Proofs and their Impact on Verified Computing

Sriram Vishwanath

10:50 AMHigh-rate spatially coupled LDPC codes based on convolutional self-orthogonal codes

Daniel Costello

Nobody Expects a Differential Equation: Minimum Energy-Per-Bit for the Gaussian Relay Channel with Rank-1 Linear Relaying

Oliver Kosut

Experiment Planning with Function Approximation

Aldo Pacchiano

Predictive modeling of maternal and neonatal outcomes

Ivana Maric

Is it easier to count communities than find them?

Cynthia Rush

11:10 AMOn performance of LDPC codes over block fading channels

Dariush Divsalar

Capacity of transmitter Trojans

Aria Nosratinia

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Quanquan Gu

In-Context Convergence of Transformers

Yingbin Liang

Approximate Causal Effect Identification under Weak Confounding

Murat Kocaoglu

11:30 AMAdaptive coding for large-scale data storage: what, why, and how?

Rashmi Vinayak

Consensus Capacity of Noisy Broadcast Channels

Neha Sangwan

Transformers Meet Image Denoising: Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals

Tan Nguyen

Zero-Correlation-Zone Sonar Sequences

Hong-Yeop Song

Reed-Muller and Polar Codes (Inv)


Info Theory 2


Individualized Decision Making (Inv)


Deep Learning and Graph Neural Nets


Privacy


1:20 PMSampling-Based Estimates of Weight Enumerators of Reed-Muller Codes

Navin Kashyap

Network Connectivity Information Freshness Tradeoff

Sennur Ulukus

Randomization Inference When N Equals One

Ben Recht

Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks

Nasimeh Heydaribeni

A New Framework for Designing Polynomial Codes for Problems in Private Information Retrieval

Alex Sprintson

1:40 PMError probability bounds for nested sequences of symmetric codes

Henry Pfister

Single-letter characterization and undecidability in network information theory

Cheuk Ting Li

Online Learning in Bandits with Predicted Context

Yongyi Guo

Information theoretic foundations of explainability in graph neural networks

Farhad Shirani

Timely offloading of private inferences

Anand Sarwate

2:00 PMDeep Polar Codes

Namyoon Lee

Vertex nomination for influence networks: application to designing microbial communities

Alfred Hero

Online Uniform Risk Times Sampling

Kyra Gan

Counting graph substructures with graph neural networks

Charilaos Kanatsoulis

Private distribution estimation through the lens of combinatorial designs

Si-Hyeon Lee

2:20 PMGenoWeave: Interleaving Polar Codes Across Strands for DNA Data Storage

Hsin-Po Wang

Some families of Jensen-like inequalities with application to information theory

Neri Merhav

When Personalization Harms Performance

Berk Ustun

Deep Learning based Cryogenic Electron Tomography: Accurate reconstruction and avoiding Hallucinations

Reinhard Heckel

Private information retrieval: algebraic construction and combinatorial capacity bounds

Ragnar Freij-Hollanti

Coding Applications


Quantum Info Theory and Algorithms


Reinforcement Learning


Wireless Communications and ML


People-centric ITA (Inv)


3:00 PMNew optimal trade-off point for coded caching systems with limited cache size

Daniela Tuninetti

Robust and Resource Efficient Quantum Communication over Bosonic Channels

Matthieu Bloch

Learning from an exploring demonstrator: Optimal inverse estimation of rewards in bandits

Vidya Muthukumar

Sequential alternating least squares approximation (SALSA) for efficient channel estimation in hybrid massive MIMO systems

Martin Haardt

Modeling and Correcting Bias in Sequential Evaluation

Jingyan Wang

3:20 PMCoexistence of eMBB and URLLC in vehicle-to-everything (V2X) communications

Homa Nikbakht

Universal framework for simultaneous tomography of quantum states and SPAM noise

Abhijith Jayakumar

Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning

R. Srikant

Inductive and Backscatter Techniques for Future IoT

David Love

Improving Diversity and Equity in San Francisco School Choice

Irene Lo

3:40 PMGradient Coding with Partial Recovery

Lalitha Vadlamani

Capacity of Classical Linear Computation over an Elemental Quantum MAC

Syed Jafar

Graph Identification for Causal Bandits

Urbashi Mitra

Computation Selection: Scheduling Users to Enable Over-the-Air Federated Learning

Bobak Nazer

AI and the Future of Optimization Modeling

Madeleine Udell

4:00 PMGame of Coding: Enabling Decentralized Learning in Trust Minimize d Settings

Mohammad Ali Maddah-Ali

Efficient quantum algorithm for solving linear systems in tensor format

Marc Vuffray

The Cost of Distributional Robustness in Reinforcement Learning: Minimax-Optimal Sample Efficiency

Laixi Shi

Structured Reinforcement Learning for Delay-Optimal Data Transmission in Dense mmWave Networks

Jian Li

What is Unique Information, and How do you Use it in Neuroscience (and Fair ML)?

Praveen Venkatesh

Wednesday

GeorgeAbeJackEvaCory
Distributed Computing and Optimization


Learning and Information Theory (Inv)


Machine Learning




9:00 AMDistributed Local Sketching for Euclidean Embeddings

Neophytos Charalambides

Output-constrained lossy source coding with application to rate-distortion-perception theory

Jun Chen

On the Tightness of Information-theoretic Bounds for Generalization Error

Jingge Zhu

9:20 AMDecentralized Sparse Matrix Multiplication Under Byzantine Attacks

Joerg Kliewer

Compression of Multisets with Bits-back Coding

Ashish Khisti

Teaching Arithmetic to Small Transformers

Dimitris Papailiopoulos

9:40 AMDistributed Structured Matrix Multiplication

Derya Malak

Beyond PCA: A Probabilistic Gram-Schmidt Approach to Feature Extraction.

Netanel Raviv

Zero-shot sampling of adversarial entities in biomedical question answering

Reza Abbasi-Asl

10:00 AMOn Graphs with Finite-Time Consensus and Their Use in Gradient Tracking

César Uribe

Quantitative group testing with tunable adaptation

Mahdi Soleymani

Towards (environmentally) responsible AI

Shaolei Ren

Graduation Day 1


Graduation Day 2


Graduation Day 3




10:40 AMA Geometric Perspective of Feature Learning

Xiangxiang Xu

New algorithms for geometrically approximating massive datasets

Naren Manoj

Data Science for Precision Health: Localization and Tracking of Neural Silences in the Brain

Alireza Chamanzar

11:00 AMGeneralization and Stability of Interpolating Neural Networks

Hossein Taheri

Stochastic variance reduction for min-max optimization

Ahmet Alacaoglu

Heterogeneous Models for Network Design and Performance Analysis in Socio-Technical Systems

Mansi Sood

11:20 AMPrincipled Out-of-Distribution Detection via Multiple Testing

Akshayaa Magesh

A first approach to noise-adaptive second-order methods

Ali Kavis

Advancing Federated Bandits by Handling Strategical Agents and Harnessing the Power of Federated Learning

Chengshuai Shi

11:40 AMA picture of the space of typical learnable tasks

Rahul Ramesh

Estimating the Rate-Distortion Function by Wasserstein Gradient Descent

Yibo Yang

Towards Reliable, Scalable and Deployable Millimeter-wave Systems

Ish Jain






Thursday

GeorgeAbeJackEvaCory
Signal processing and quantum systems (Inv)


High Dimensional Statistics


Differential Privacy


Generative AI


Statistical Learning and Estimation


10:30 AMMaximum Likelihood Quantum Error Mitigation for Algorithms with a Single Correct Output

Dror Baron

Binomial Empirical Processe

Aryeh Kontorovich

Optimal binary differential privacy via graphs

Parastoo Sadeghi

DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Rose Yu

Data-Driven Estimation of the Optimal Performance of Classifiers via Soft Labels

Martina Cardone

10:50 AMTheory and applications of hybrid discrete and continuous-variable quantum signal processing

Yuan Liu

Kernel Ridge Regression in the Quadratic Regime

Yizhe Zhu

Scaling up Private Causal Graph Discovery via Adaptive Privacy Budgeting

Ravi Tandon

Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models

Mahdi Soltanolkotabi

Time to Model Collapse in Recursive Training

Andrew Thangaraj

11:10 AMQuantum Signal Processing in Noisy Intermediate-Scale Quantum (NISQ) Devices

Victor M. Bastidas

Efficient reductions between some statistical models

Ashwin Pananjady

Auditing f-DP in one run

Saeed Mahloujifar

The emergence of reproducibility and consistency in diffusion models

Qing Qu

Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing

Yihan Zhang

11:30 AMFeedback-based quantum algorithms

Alicia Magann

On the Noise Sensitivity of the Randomized SVD

Elad Romanov

Learning a conditional generative model in total variation

Ajil Jalal

Statistical-Computational Trade-offs for Density Estimation

Alexandr Andoni

Wireless Communications


Control


Private Optimization with Correlated Noise (Inv)


Machine Learning and LLMs


Optimization, Sampling, and Games from Classical Mechanics (Inv)


1:20 PMFog Learning under Heterogeneity: The Role of Ad-Hoc Wireless Topologies

Christopher Brinton

Value of Information: A Novel Metric for Networked Control Systems Tasks

John Baras

Overview of Correlated Noise Mechanisms and DP-Follow-the-regularized-leader

Abhradeep Guha Thakurta

Implicit Bias of Next-Token Prediction

Christos Thrampoulidis

Alternating Mirror Descent for Constrained Min-Max Games

Andre Wibisono

1:40 PMAchieving optimum received power in the smallest number of steps for discrete-phase RISs

Ender Ayanoglu

What network science can offer public health

Saswati Sarkar

Correlated Noise Provably Beats Independent Noise for Differentially Private Learning

Krishnamurthy Dvijotham

Transformers learn higher-order optimization methods for in-context learning: A study with linear models

Vatsal Sharan

Sampling & physics: from classical dynamical system to modern diffusion models

Qijia Jiang

2:00 PMHybrid arrays: how many RF chains are required to prevent beam squint?

Heedong Do

Controlled sensing for communication-efficient estimation in POMDPs

Girish Nair

(Amplified) Banded Matrix Factorization: A unified approach to private training

Arun Ganesh

Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features

Marco Mondelli

Hamiltonian descent and coordinate Hamiltonian descent

Jun-Kun Wang

2:20 PMVariational Bayes for MIMO detection with unquantized and quantized receptions

Duy Nguyen

Transformers for Kalman filtering and control

Gautam Goel

Federated Learning of Gboard Language Models with Differential Privacy

Zheng Xu

Understanding Self-Distillation and Partial Label Learning in Multi-Class Classification with Label Noise

Hye Won Chung

Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm

Ashia Wilson

Graph Signal Processing (Inv)


Learning/Optimization/Control in Smart Grids (Inv)


Machine Learning and Privacy


Representation Learning


Bandits


3:00 PMGraph filter and GNN design in the presence of graph perturbations

Antonio Marques

Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis

Yingying Li

The importance of feature preprocessing for differentially private linear optimization

Ananda Suresh

Deja-vu: Measuring Memorization in Representation Learning

Kamalika Chaudhuri

Global optimization with parametric function approximation: realizability and misspecification

Chong Liu

3:20 PMLearning Graphs and Simplicial Complexes from Data

Geert Leus

Synchro-Waveform Data Analysis in Power Systems

Hamed Mohsenian-Rad

All Rivers Run to the Sea: Private Learning with Asymmetric Flows

Ramy Ali

Learning Robust Representations: Latent Feature Disentanglement vs Multi-Expert Adversarial Regularization

Mostafa El-Khamy

Multi-Fidelity Multi-Armed Bandits Revisited

Xuchuang Wang

3:40 PMDemystifying and Mitigating Unfairness for Learning over Graphs

Yanning Shen

Stability-constrained Reinforcement Learning for Sustainable Energy Systems

Yuanyuan Shi

PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses

Adel Javanmard

Learning invariant representations under general interventions on the response

Yu Xiang

Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders

Mahsa Ghasemi

4:00 PMMaximizing Reachability in Factored MDPs via Near-Optimal Clustering with Applications to Control of Multi-Agent Systems

Bruno Sinopoli

Fast Risk Assessment in Power Grids through Network-aware Gaussian Processes

Deepjyoti Deka

Training generative models from privatized data via Entropic Optimal Transport

Ayfer Ozgur

Revisiting hard negative sampling for contrastive learning: Optimal representation geometry and neural vs dimensional collapse

Shuchin Aeron

Adversarial Attacks on Cooperative Multi-agent Bandits

Jinhang Zuo

Friday

GeorgeAbeJackEvaCory
LLMs and Machine Learning


Machine Learning 1


Optimization


Coding


Game Theory and Resource Allocation


10:30 AMAttention with Markov: A Framework for Principled Analysis of Transformers via Markov Chains

Ashok Vardhan Makkuva

Understanding Hierarchical Representations in Deep Networks via Feature Compression and Discrimination

Peng Wang

Operator SVD with neural networks via nested low-rank approximation

Jongha (Jon) Ryu

On best short wiretap coset codes

Willie Harrison

Port Capacity Leasing Games at Internet Exchange Points

Koushik Kar

10:50 AMIn-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness

Aryan Mokhtari

Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data

Abolfazl Hashemi

Differentially Privacy Meets Adaptive Optimization

Tian Li

Efficient List-decoding of Polynomial Ideal Codes with Optimal List Size

Mary Wootters

Market Impacts of Pooling Intermittent Spectrum

Randall Berry

11:10 AMProvably learning a multi-head attention layer

Sitan Chen

Reliable Counterfactual Explanations Under Model Multiplicity

Sanghamitra Dutta

Sharp global convergence guarantees for iterative nonconvex optimization with random data

Kabir Verchand

Outperforming 5G LDPC codes via Soft Output GRAND

Ken Duffy

Incentivizing Secure Software Development: The Role of Liability (Waiver) and Audit

Mingyan Liu

11:30 AMRegularization and Optimal Multiclass Learning

Shaddin Dughmi

Continuous-time neural networks can stably memorize random spike trains

Hans-Andrea Loeliger

The landscape and sample complexity of quadratic feasibility

Gautam Dasarathy

Online Budgeted Allocation: Worst Case Guarantee and Learning Augmentation

Jianyi Yang

Large Language Models (Inv)


Neural Nets


Optimization and control in multi-agent systems (Inv)


Coding and Security (Inv)


Machine Learning 2


1:20 PMUnderstanding Self-Attention as a Context-Conditioned Markov Chain

Samet Oymak

Information-Theoretic Generalization Bounds for Deep Neural Networks

Haiyun He

On the Nash Equilibria of Multiplex and Multilayer Network Games

Parinaz Naghizadeh

Leveraging AES padding: dBs for nothing and FEC for free in IoT systems

Muriel Medard

A unified framework for information-theoretic generalization bounds

Maxim Raginsky

1:40 PMLanguage Model Alignment: Theory & Practice

Ahmad Beirami

How Transformers Learn Causal Structure with Gradient Descent

Jason Lee

Benign Nonconvex Landscapes in Optimal and Robust Control

Yang Zheng

Introducing Spice

Rafael D'Oliveira

How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers

Nathan Srebro

2:00 PMSpecTr: Fast Speculative Decoding via Optimal Transport

Ziteng Sun

Smooth Activations and Reproducibility in Deep Networks

Gil Shamir

Logarithmic Communication for Distributed Optimization in Multi-Agent Systems

Palma London

CRYPTO-MINE: Cryptanalysis via Mutual Information Neural Estimation

Vipindev Adat Vasudevan

Promises and Pitfalls of Threshold-based Auto-labeling

Ramya Korlakai Vinayak

2:20 PMWatermarking LLMs with Permute-and-Flip Sampling

Yu-Xiang Wang

How to Review Peer Reviews? Experiments, Theory and Deployment

Nihar Shah

A Theory for Allocating Autonomous Systems

Jason Marden

Are activation functions required for learning in all deep networks?

Grigorios Chrysos

Machine Learning and Efficiency



Adaptive and stochastic optimization (Inv)


Optimization, Control and RL


Communication, Inference and Optimization


3:00 PMThe Expressive Power of Low-Rank Adaptation (LoRA)

Kangwook Lee

Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models

Mladen Kolar

Data-Driven Control with Inherent Lyapunov Stability

Navid Azizan

Remote Inference for Safety

Yin Sun

3:20 PMProvable Computational and Sample Efficiency of the Sparse Mixture of Experts Architecture

Meng Wang

From Stability to Chaos: Analyzing Gradient Descent Dynamics in Quadratic Regression

Krishnakumar Balasubramanian

Robust 1-bit Compressed Sensing with Iterative Hard Thresholding

Arya Mazumdar

Clustered Switchback Experiments: Near-Optimal Rates Under Spatiotemporal Interference

Su Jia

3:40 PMEfficient Learning of Linear Graph Neural Networks via Node Subsampling

Ilan Shomorony

Multiplicative noise and heavy tails in stochastic optimization and machine learning

Michael Mahoney

Principled Penalty-based Bilevel Methods for RLHF

Tianyi Chen

An interactive control strategy improves information transfer rate in noisy control systems

Virginia de Sa

4:00 PMWeight matrix diagnostics and improved neural network training

Yaoqing Yang

Why does SGD converge so fast on over-parameterized neural networks?

Chaoyue Liu

Model-Free, Regret-Optimal BPI in Online CMDPs

Lei Ying

Towards Optimal Distributionally Robust Stochastic Optimization

Zaid Harchaoui