Impact of topology on interference networks with no CSIT. - Navid Naderializadeh; Amir Salman Avestimehr (ISIT, 2013)

How to utilize caching to improve spectral efficiency in device-to-device wireless networks. - Navid Naderializadeh; David T. H. Kao; Amir Salman Avestimehr (Allerton, 2014)

ITLinQ: A new approach for spectrum sharing. - Navid Naderializadeh; Amir Salman Avestimehr (DySPAN, 2014)

ITLinQ: A New Approach for Spectrum Sharing in Device-to-Device Communication Systems. - Navid Naderializadeh; Amir Salman Avestimehr (IEEE J. Sel. Areas Commun., 2014)

Topological interference management with just retransmission: What are the "Best" topologies? - Navid Naderializadeh; Aly El Gamal; Amir Salman Avestimehr (ICC, 2015)

When does an ensemble of matrices with randomly scaled rows lose rank? - Aly El Gamal; Navid Naderializadeh; Amir Salman Avestimehr (ISIT, 2015)

On the Optimality of Treating Interference as Noise. - Chunhua Geng; Navid Naderializadeh; Amir Salman Avestimehr; Syed Ali Jafar (IEEE Trans. Inf. Theory, 2015)

Interference Networks With no CSIT: Impact of Topology. - Navid Naderializadeh; Amir Salman Avestimehr (IEEE Trans. Inf. Theory, 2015)

On the optimality of separation between caching and delivery in general cache networks. - Navid Naderializadeh; Mohammad Ali Maddah-Ali; Amir Salman Avestimehr (ISIT, 2017)

Ultra-Dense Networks in 5G: Interference Management via Non-Orthogonal Multiple Access and Treating Interference as Noise. - Navid Naderializadeh; Oner Orhan; Hosein Nikopour; Shilpa Talwar (VTC Fall, 2017)

Topological Interference Management With Reconfigurable Antennas. - Heecheol Yang; Navid Naderializadeh; Amir Salman Avestimehr; Jungwoo Lee 001 (IEEE Trans. Commun., 2017)

Fundamental Limits of Non-Coherent Interference Alignment via Matroid Theory. - Navid Naderializadeh; Aly El Gamal; Amir Salman Avestimehr (IEEE Trans. Inf. Theory, 2017)

Fundamental Limits of Cache-Aided Interference Management. - Navid Naderializadeh; Mohammad Ali Maddah-Ali; Amir Salman Avestimehr (IEEE Trans. Inf. Theory, 2017)

Feedback-Based Interference Management in Ultra-Dense Networks via Parallel Dynamic Cell Selection and Link Scheduling. - Navid Naderializadeh; Hosein Nikopour; Oner Orhan; Shilpa Talwar (ICC, 2018)

Learning to Code: Coded Caching via Deep Reinforcement Learning. - Navid Naderializadeh; Seyed Mohammad Asghari (ACSSC, 2019)

Energy-Aware Multi-Server Mobile Edge Computing: A Deep Reinforcement Learning Approach. - Navid Naderializadeh; Morteza Hashemi (ACSSC, 2019)

Deep CNN for Wideband Mmwave Massive Mimo Channel Estimation Using Frequency Correlation. - Peihao Dong; Hua Zhang 002; Geoffrey Ye Li; Navid Naderializadeh; Ivan Simões Gaspar (ICASSP, 2019)

Monitoring Under-Modeled Rare Events for URLLC. - Vasuki Narasimha Swamy; Navid Naderializadeh; Venkatesan Nallampatti Ekambaram; Shilpa Talwar; Anant Sahai (SPAWC, 2019)

A Power Efficient Fully Digital Beamforming Architecture for mmWave Communications. - Oner Orhan; Hosein Nikopour; Junyoung Nam; Navid Naderializadeh; Shilpa Talwar (VTC Spring, 2019)

When Multiple Agents Learn to Schedule: A Distributed Radio Resource Management Framework. - Navid Naderializadeh; Jaroslaw J. Sydir; Meryem Simsek; Hosein Nikopour; Shilpa Talwar (CoRR, 2019)

Deep CNN-Based Channel Estimation for mmWave Massive MIMO Systems. - Peihao Dong; Hua Zhang 002; Geoffrey Ye Li; Ivan Simões Gaspar; Navid Naderializadeh (IEEE J. Sel. Top. Signal Process., 2019)

Cache-Aided Interference Management in Wireless Cellular Networks. - Navid Naderializadeh; Mohammad Ali Maddah-Ali; Amir Salman Avestimehr (IEEE Trans. Commun., 2019)

Wireless Power Control via Counterfactual Optimization of Graph Neural Networks. - Navid Naderializadeh; Mark Eisen; Alejandro Ribeiro (SPAWC, 2020)

On the Communication Latency of Wireless Decentralized Learning. - Navid Naderializadeh (CoRR, 2020)

Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning. - Navid Naderializadeh; Fan H. Hung; Sean Soleyman; Deepak Khosla (CoRR, 2020)

Optimizing the Configuration of Intelligent Reflecting Surfaces using Deep Learning. - Chuan Sun; Navid Naderializadeh; Morteza Hashemi (GLOBECOM (Workshops), 2021)

Contrastive Self-Supervised Learning for Wireless Power Control. - Navid Naderializadeh (ICASSP, 2021)

Wasserstein Embedding for Graph Learning. - Soheil Kolouri; Navid Naderializadeh; Gustavo K. Rohde; Heiko Hoffmann (ICLR, 2021)

Pooling by Sliced-Wasserstein Embedding. - Navid Naderializadeh; Joseph F. Comer; Reed W. Andrews; Heiko Hoffmann; Soheil Kolouri (NeurIPS, 2021)

Set Representation Learning with Generalized Sliced-Wasserstein Embeddings. - Navid Naderializadeh; Soheil Kolouri; Joseph F. Comer; Reed W. Andrews; Heiko Hoffmann (CoRR, 2021)

Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision Levels. - Navid Naderializadeh (CoRR, 2021)

Resource Management in Wireless Networks via Multi-Agent Deep Reinforcement Learning. - Navid Naderializadeh; Jaroslaw J. Sydir; Meryem Simsek; Hosein Nikopour (IEEE Trans. Wirel. Commun., 2021)

Adaptive Wireless Power Allocation with Graph Neural Networks. - Navid Naderializadeh; Mark Eisen; Alejandro Ribeiro (ICASSP, 2022)

A Lagrangian Duality Approach to Active Learning. - Juan Elenter; Navid Naderializadeh; Alejandro Ribeiro (NeurIPS, 2022)

Federated Representation Learning via Maximal Coding Rate Reduction. - Juan Cerviño; Navid Naderializadeh; Alejandro Ribeiro (CoRR, 2022)

A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks. - Yigit Berkay Uslu; Navid Naderializadeh; Mark Eisen; Alejandro Ribeiro (CoRR, 2022)

Guest Editorial: An End-to-End Machine Learning Perspective on Industrial IoT. - Rita H. Wouhaybi; Ravikumar Balakrishnan; Navid Naderializadeh; Ahmad Beirami; Marco Di Felice; Shadi A. Noghabi; Anirudh Badam; Shugong Xu (IEEE Internet Things Mag., 2022)

State-Augmented Learnable Algorithms for Resource Management in Wireless Networks. - Navid Naderializadeh; Mark Eisen; Alejandro Ribeiro (IEEE Trans. Signal Process., 2022)

Stochastic Unrolled Federated Learning. - Samar Hadou; Navid Naderializadeh; Alejandro Ribeiro (CoRR, 2023)

Primal-Dual Continual Learning: Stability and Plasticity through Lagrange Multipliers. - Juan Elenter; Navid Naderializadeh; Tara Javidi; Alejandro Ribeiro (CoRR, 2023)

Learning Resilient Radio Resource Management Policies With Graph Neural Networks. - Navid Naderializadeh; Mark Eisen; Alejandro Ribeiro (IEEE Trans. Signal Process., 2023)

Learning to Slice Wi-Fi Networks: A State-Augmented Primal-Dual Approach. - Yigit Berkay Uslu; Roya Doostnejad; Alejandro Ribeiro; Navid Naderializadeh (GLOBECOM, 2024)

State-Augmented Information Routing In Communication Systems With Graph Neural Networks. - Sourajit Das; Navid Naderializadeh; Alejandro Ribeiro (ICASSP, 2024)

Decentralized Learning Strategies for Estimation Error Minimization with Graph Neural Networks. - Xingran Chen; Navid Naderializadeh; Alejandro Ribeiro; Shirin Saeedi Bidokhti (CoRR, 2024)

Robust Stochastically-Descending Unrolled Networks. - Samar Hadou; Navid Naderializadeh; Alejandro Ribeiro (IEEE Trans. Signal Process., 2024)

State-Augmented Opportunistic Routing in Wireless Communication Systems with Graph Neural Networks. - Sourajit Das; Navid Naderializadeh; Alejandro Ribeiro (ICASSP, 2025)

Learning State-Augmented Policies for Information Routing in Communication Networks. - Sourajit Das; Navid Naderializadeh; Alejandro Ribeiro (IEEE Trans. Signal Process., 2025)

ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans. - Ashkan Shahbazi; Elaheh Akbari; Darian Salehi; Xinran Liu; Navid Naderializadeh; Soheil Kolouri (CoRR, 2025)

Opportunistic Routing in Wireless Communications via Learnable State-Augmented Policies. - Sourajit Das; Navid Naderializadeh; Rahul Mangharam; Alejandro Ribeiro (CoRR, 2025)

Constrained Sliced Wasserstein Embedding. - Navid Naderializadeh; Darian Salehi; Xinran Liu; Soheil Kolouri (CoRR, 2025)

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression. - Yigit Berkay Uslu; Navid Naderializadeh; Mark Eisen; Alejandro Ribeiro (CoRR, 2025)