Tianyi Chen

Orcid: 0000-0003-3477-1439

Affiliations:
  • Cornell University, Department of Electrical and Computer Engineering, New York, NY, USA


According to our database1, Tianyi Chen authored at least 124 papers between 2014 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies.
CoRR, March, 2026

SiMPO: Measure Matching for Online Diffusion Reinforcement Learning.
CoRR, March, 2026

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training.
CoRR, February, 2026

On the Convergence Theory of Pipeline Gradient-Based Analog In-Memory Training.
IEEE J. Sel. Areas Inf. Theory, 2026

2025
On penalty-based bilevel gradient descent method.
Math. Program., November, 2025

Mitigating Modality Imbalance in Multi-modal Learning via Multi-objective Optimization.
CoRR, November, 2025

In-memory Training on Analog Devices with Limited Conductance States via Multi-tile Residual Learning.
CoRR, October, 2025

Self-Supervised Pre-Training with Equilibrium Constraints.
CoRR, August, 2025

Objective Soups: Multilingual Multi-Task Modeling for Speech Processing.
CoRR, August, 2025

One-Step Flow Policy Mirror Descent.
CoRR, July, 2025

Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions.
CoRR, February, 2025

Soft Diffusion Actor-Critic: Efficient Online Reinforcement Learning for Diffusion Policy.
CoRR, February, 2025

A First-order Generative Bilevel Optimization Framework for Diffusion Models.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

Efficient Online Reinforcement Learning for Diffusion Policy.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

Primal-Dual Spectral Representation for Off-policy Evaluation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024
Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation.
Trans. Mach. Learn. Res., 2024

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition.
CoRR, 2024

Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning.
CoRR, 2024

Pipeline Gradient-based Model Training on Analog In-memory Accelerators.
CoRR, 2024

Towards Exact Gradient-based Training on Analog In-memory Computing.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

M2ASR: Multilingual Multi-task Automatic Speech Recognition via Multi-objective Optimization.
Proceedings of the 25th Annual Conference of the International Speech Communication Association, 2024

SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Method for Bilevel Optimization with Convex Lower-Level Problem.
Proceedings of the IEEE International Conference on Acoustics, 2024

Joint Unsupervised and Supervised Training for Automatic Speech Recognition via Bilevel Optimization.
Proceedings of the IEEE International Conference on Acoustics, 2024

Variance Reduction Can Improve Trade-Off in Multi-Objective Learning.
Proceedings of the IEEE International Conference on Acoustics, 2024

Leveraging Large Language Models for Wireless Symbol Detection via In-Context Learning.
Proceedings of the 2024 IEEE Global Communications Conference, 2024

Transferable Learning of GCN Sampling Graph Data Clusters from Different Power Systems.
Proceedings of the 60th Annual Allerton Conference on Communication, 2024

Enhancing In-context Learning via Linear Probe Calibration.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Lazy Queries Can Reduce Variance in Zeroth-Order Optimization.
IEEE Trans. Signal Process., 2023

Byzantine-Resilient Decentralized Stochastic Optimization With Robust Aggregation Rules.
IEEE Trans. Signal Process., 2023

Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup.
IEEE Trans. Signal Process., 2023

Learning with Limited Samples: Meta-Learning and Applications to Communication Systems.
Found. Trends Signal Process., 2023

Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Nested Ensemble Method to Bilevel Machine Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

On the Stability Analysis of Open Federated Learning Systems.
Proceedings of the American Control Conference, 2023

Alternating Projected SGD for Equality-constrained Bilevel Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Communication-Censored Distributed Stochastic Gradient Descent.
IEEE Trans. Neural Networks Learn. Syst., 2022

Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning.
IEEE Trans. Control. Netw. Syst., 2022

Adaptive Temporal Difference Learning With Linear Function Approximation.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Byzantine-robust variance-reduced federated learning over distributed non-i.i.d. data.
Inf. Sci., 2022

Alternating Implicit Projected SGD and Its Efficient Variants for Equality-constrained Bilevel Optimization.
CoRR, 2022

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach.
CoRR, 2022

Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees.
Proceedings of the Learning for Dynamics and Control Conference, 2022

Federated Multi-Armed Bandit Via Uncoordinated Exploration.
Proceedings of the IEEE International Conference on Acoustics, 2022

A Single-Timescale Method for Stochastic Bilevel Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Data Leakage in Federated Learning.
Proceedings of the Federated Learning, 2022

2021
Edge-Centric Bandit Learning for Task-Offloading Allocations in Multi-RAT Heterogeneous Networks.
IEEE Trans. Veh. Technol., 2021

Byzantine-Resilient Decentralized Policy Evaluation With Linear Function Approximation.
IEEE Trans. Signal Process., 2021

Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization.
IEEE Trans. Signal Process., 2021

Communication-Adaptive Stochastic Gradient Methods for Distributed Learning.
IEEE Trans. Signal Process., 2021

Multi-Agent Multi-Armed Bandit Learning for Online Management of Edge-Assisted Computing.
IEEE Trans. Commun., 2021

Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems.
CoRR, 2021

Connected and Automated Vehicle Distributed Control for On-ramp Merging Scenario: A Virtual Rotation Approach.
CoRR, 2021

A Single-Timescale Stochastic Bilevel Optimization Method.
CoRR, 2021

Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Byzantine-Resilient Decentralized TD Learning with Linear Function Approximation.
Proceedings of the IEEE International Conference on Acoustics, 2021

An Optimal Stochastic Compositional Optimization Method with Applications to Meta Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

CADA: Communication-Adaptive Distributed Adam.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks.
IEEE Trans. Signal Process., 2020

Asynchronous Advantage Actor Critic: Non-asymptotic Analysis and Linear Speedup.
CoRR, 2020

Hybrid Federated Learning: Algorithms and Implementation.
CoRR, 2020

VAFL: a Method of Vertical Asynchronous Federated Learning.
CoRR, 2020

Communication-Efficient Robust Federated Learning Over Heterogeneous Datasets.
CoRR, 2020

LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning.
CoRR, 2020

An MAB Approach for MEC-centric Task-offloading Control in Multi-RAT HetNets.
Proceedings of the 2020 IEEE International Conference on Communications, 2020

Resilient to Byzantine Attacks Finite-Sum Optimization Over Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

A Combinatorial Bandit Approach to UAV-aided Edge Computing.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Secure Mobile Edge Computing in IoT via Collaborative Online Learning.
IEEE Trans. Signal Process., 2019

Real-Time Energy Management in Microgrids With Reduced Battery Capacity Requirements.
IEEE Trans. Smart Grid, 2019

Multi-Timescale Online Optimization of Network Function Virtualization for Service Chaining.
IEEE Trans. Mob. Comput., 2019

Learning and Management for Internet of Things: Accounting for Adaptivity and Scalability.
Proc. IEEE, 2019

Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics.
J. Mach. Learn. Res., 2019

Bandit Convex Optimization for Scalable and Dynamic IoT Management.
IEEE Internet Things J., 2019

Decentralized Markov Chain Gradient Descent.
CoRR, 2019

Communication-Censored Distributed Stochastic Gradient Descent.
CoRR, 2019

Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Byzantine-Robust Stochastic Gradient Descent for Distributed Low-Rank Matrix Completion.
Proceedings of the IEEE Data Science Workshop, 2019

Bandit Online Learning with Unknown Delays.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Two-Scale Stochastic Control for Integrated Multipoint Communication Systems With Renewables.
IEEE Trans. Smart Grid, 2018

Learn-and-Adapt Stochastic Dual Gradients for Network Resource Allocation.
IEEE Trans. Control. Netw. Syst., 2018

Heterogeneous Online Learning for "Thing-Adaptive" Fog Computing in IoT.
IEEE Internet Things J., 2018

Communication-Efficient Distributed Reinforcement Learning.
CoRR, 2018

Delayed Bandit Online Learning with Unknown Delays.
CoRR, 2018

Online Learning Adaptive to Dynamic and Adversarial Environments.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Multi-Kernel Learning with Orthogonal Random Features.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Harnessing Bandit Online Learning to Low-Latency Fog Computing.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Aggregating Flexibility of Heterogeneous Energy Resources in Distribution Networks.
Proceedings of the 2018 Annual American Control Conference, 2018

Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Secure Edge Computing in IoT via Online Learning.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017
Real-Time Energy Trading and Future Planning for Fifth Generation Wireless Communications.
IEEE Wirel. Commun., 2017

Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation.
IEEE Trans. Signal Process., 2017

An Online Convex Optimization Approach to Proactive Network Resource Allocation.
IEEE Trans. Signal Process., 2017

DGLB: Distributed Stochastic Geographical Load Balancing over Cloud Networks.
IEEE Trans. Parallel Distributed Syst., 2017

An Online Convex Optimization Approach to Dynamic Network Resource Allocation.
CoRR, 2017

Learn-and-adapt network resource allocation.
Proceedings of the 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2017

Distributed Stochastic Optimization of Network Function Virtualization.
Proceedings of the 2017 IEEE Global Communications Conference, 2017

Real-time energy management with improved cost-capacity tradeoff.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

Online convex optimization for dynamic network resource allocation.
Proceedings of the 25th European Signal Processing Conference, 2017

Online learning for "thing-adaptive" Fog Computing in IoT.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016
Energy-Efficient Transmission Schedule for Delay-Limited Bursty Data Arrivals Under Nonideal Circuit Power Consumption.
IEEE Trans. Veh. Technol., 2016

Cooling-Aware Energy and Workload Management in Data Centers via Stochastic Optimization.
IEEE J. Sel. Top. Signal Process., 2016

Dynamic Energy Management for Smart-Grid-Powered Coordinated Multipoint Systems.
IEEE J. Sel. Areas Commun., 2016

Dynamic Resource Allocation for Smart-Grid Powered MIMO Downlink Transmissions.
IEEE J. Sel. Areas Commun., 2016

Robust Workload and Energy Management for Sustainable Data Centers.
IEEE J. Sel. Areas Commun., 2016

Two-Scale Stochastic Control for Multipoint Communication Systems with Renewables.
CoRR, 2016

Robust geographical load balancing for sustainable data centers.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Stochastic online control for smart-grid powered MIMO downlink transmissions.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Two-Scale Stochastic Control for Smart-Grid Powered Coordinated Multi-Point Systems.
Proceedings of the 2016 IEEE Global Communications Conference, 2016

A data-driven approach to stochastic network optimization.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Space-time scheduling for green data center networks.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Optimal MIMO Broadcasting for Energy Harvesting Transmitter With non-Ideal Circuit Power Consumption.
IEEE Trans. Wirel. Commun., 2015

Optimal Scheduling for Wireless On-Demand Data Packet Delivery to High-Speed Trains.
IEEE Trans. Veh. Technol., 2015

Optimal Dynamic Power Management for Green Coordinated Multipoint Systems.
Proceedings of the 2015 IEEE Global Communications Conference, 2015

Energy and workload management for data centers in renewable-integrated power grid.
Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015

2014
Energy-Efficient Transmission Schedule for Delay-Limited Bursty Data Arrivals under Non-Ideal Circuit Power Consumption.
CoRR, 2014

Optimal MIMO broadcasting over time-varying wireless channels for energy harvesting transmitter with non-ideal circuit power.
Proceedings of the IEEE International Conference on Acoustics, 2014

Energy-efficient transmission of delay-limited bursty data packets over time-varying channels under non-ideal circuit power.
Proceedings of the IEEE China Summit & International Conference on Signal and Information Processing, 2014


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