Amir Yazdanbakhsh
16 papers · 2020–2026 · 5 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (24) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 👥 Mega-Team · Squad
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Mega-Team · Squad
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Keyword Collector
(76)
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Unstoppable · Bronze
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The Questioner
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Prolific Year · Productive
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Century Club · Bronze
Venues
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Research topics
Machine Learning
(14)
Artificial Intelligence
(12)
Core AI
(11)
Application Areas
(9)
Deep Learning
(7)
Natural Language Processing
(7)
Optimization & Theory · Machine Learning
(6)
Generation
(5)
Learning Types
(4)
Models
(2)
Optimization & Theory · Deep Learning
(2)
Resources & Methods
(2)
Techniques
(2)
Computer Science
(1)
Applications
(1)
Keywords
large language model
(5)
model compression
(5)
few-shot learning
(2)
neural network pruning
(2)
code optimization
(2)
sparse pre-training
(2)
text generation
(1)
variance estimation
(1)
in-context learning
(1)
sparsity
(1)
computational cost
(1)
structured sparsity
(1)
memory efficiency
(1)
adam optimizer
(1)
low-rank approximation
(1)
weight pruning
(1)
inference optimization
(1)
iterative refinement
(1)
scaling law
(1)
language model
(1)
Papers
ECO: An AI-Driven Code Efficiency Optimizer for Warehouse Scale Computers (Operational Systems)
OSDI 2026
Effective Interplay between Sparsity and Quantization: From Theory to Practice
ICLR 2025
Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding
ICML 2025
SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression
ICML 2025
SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs
ICLR 2025
SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity
ICML 2025
The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws
ICLR 2025
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
NeurIPS 2024
Learning Performance-Improving Code Edits
ICLR 2024
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
NeurIPS 2024
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
ICML 2024
Self-Refine: Iterative Refinement with Self-Feedback
NeurIPS 2023
STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
ICML 2023
What Makes Chain-of-Thought Prompting Effective? A Counterfactual Study
EMNLP 2023
Data-Driven Offline Optimization for Architecting Hardware Accelerators
ICLR 2022
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation
ICLR 2020