← Authors

Dimitris Papailiopoulos

43 papers · 2013–2025 · 7 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) 🐝 Cross-Pollinator (12) πŸƒ Academic Marathon (12) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (12) 🌈 Renaissance Researcher (7) 🀝 Dynamic Duo (15) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ’Ž Century Club (43) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (8) ⚑ Prolific Year (5) ❓ The Questioner (4) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (154)

Conferences

ICML (16) NIPS (14) AISTATS (5) ICLR (5) ACL (1) COLT (1) EMNLP (1)

Top co-authors

Kangwook Lee (15) Shashank Rajput (12) Jy-yong Sohn (7) Hongyi Wang (7) Zachary Charles (6) Kartik Sreenivasan (6) Angeliki Giannou (5) Samet Oymak (5) Kannan Ramchandran (4) Megasthenis Asteris (4)

Keywords

stochastic gradient descent (3) in-context learning (3) relu network (3) neural network pruning (3) approximation algorithm (3) combinatorial optimization (3) distributed training (3) generalization bound (2) eigenvalue decay (2) adversarial perturbation (2) sparse pca (2) model compression (2) graph clustering (2) lottery ticket hypothesis (2) distributed learning (2) attention mechanism (2) data augmentation (2) gradient aggregation (2) sparse principal component analysis (2) correlation clustering (2)

Papers

Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries ICML 2025
How Well Can Transformers Emulate In-Context Newton’s Method? AISTATS 2025
Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges ICML 2025
From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data ICLR 2025
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data ICML 2025
Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition ICML 2025
Can Mamba Learn How To Learn? A Comparative Study on In-Context Learning Tasks ICML 2024
Looped Transformers are Better at Learning Learning Algorithms ICLR 2024
Teaching Arithmetic to Small Transformers ICLR 2024
CHAI: Clustered Head Attention for Efficient LLM Inference ICML 2024
Prompted LLMs as Chatbot Modules for Long Open-domain Conversation ACL 2023
The Expressive Power of Tuning Only the Normalization Layers COLT 2023
Transformers as Algorithms: Generalization and Stability in In-context Learning ICML 2023
Looped Transformers as Programmable Computers ICML 2023
Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning NIPS 2023
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment EMNLP 2022
LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks NIPS 2022
Rare Gems: Finding Lottery Tickets at Initialization NIPS 2022
Finding Nearly Everything within Random Binary Networks AISTATS 2022
Permutation-Based SGD: Is Random Optimal? ICLR 2022
GenLabel: Mixup Relabeling using Generative Models ICML 2022
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks NIPS 2021
Closing the convergence gap of SGD without replacement ICML 2020
Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient NIPS 2020
Bad Global Minima Exist and SGD Can Reach Them NIPS 2020
Federated Learning with Matched Averaging ICLR 2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning NIPS 2020
Does Data Augmentation Lead to Positive Margin? ICML 2019
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation NIPS 2019
A Geometric Perspective on the Transferability of Adversarial Directions AISTATS 2019
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning AISTATS 2018
Stability and Generalization of Learning Algorithms that Converge to Global Optima ICML 2018
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients ICML 2018
The Effect of Network Width on the Performance of Large-batch Training NIPS 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification NIPS 2018
Cyclades: Conflict-free Asynchronous Machine Learning NIPS 2016
Bipartite Correlation Clustering: Maximizing Agreements AISTATS 2016
Sparse PCA via Bipartite Matchings NIPS 2015
Parallel Correlation Clustering on Big Graphs NIPS 2015
Orthogonal NMF through Subspace Exploration NIPS 2015
Finding Dense Subgraphs via Low-Rank Bilinear Optimization ICML 2014
Nonnegative Sparse PCA with Provable Guarantees ICML 2014
Sparse PCA through Low-rank Approximations ICML 2013