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Monday, June 28th, 2021 |
| Time |
Room 1 |
Room 2 |
Room 3 |
Room 4 |
Room 5 |
Room 6 |
Room 7 |
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10:00AM |
BPA1: Best paper awards - I (Student) |
T9: Evolutionary Computation for Feature Reduction |
T16: Introduction to Grammar-Based Evolutionary Computation |
T22: Evolutionary Machine Learning |
T6: Statistical Analyses for Meta-heuristic Stochastic Optimization Algorithms |
T8: Cartesian Genetic Programming and its Applications |
T20: Evolutionary Computation for Digital Art |
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12:00PM |
BPA2: Best paper awards - II (General) |
T2: Towards Better Explainable AI Through Genetic Programming |
T23: Embedding Knowledge into Optimization Process |
T10: Pareto Optimization for Subset Selection: Theories and Practical Algorithms |
T11: Modern Linkage Learning Techniques in Combinatorial Optimization |
T12: Differential Evolution with Ensembles, Adaptations and Topologies |
T24: Evolutionary Diversity Optimization |
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2:00PM |
Break |
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2:15PM |
T14: Large-Scale Optimization and Learning |
T15: Multiobjective Optimization in the Presence of Constraints |
T4: Game Dynamics on Evolutionary Graphs: An Introduction |
T17: Benchmarking and Experimentation: Pitfalls and Best Practices |
T18: An Easy Introduction to Theory of Evolutionary Computation |
T3: Advances in Particle Swarm Optimization Development, Analysis, and Understanding |
W1: Workshop on Selection |
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4:15PM |
T1: Evolutionary Algorithms and Hyper-Heuristics |
T19: Evolution of Neural Networks |
T21: Adversarial Deep Learning by Using Coevolutionary Computation |
T5: Evolutionary Bilevel Optimization |
T7: Metaheuristics for NP-hard Combinatorial Problems |
T13: Evolutionary Many-Objective Optimization |
W2: Good Benchmarking Practices for Evolutionary Computation- BENCHMARKING@CEC-2021 |
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6:15PM |
End of day |
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Tuesday, June 29th, 2021 |
| Time |
Room 1 |
Room 2 |
Room 3 |
Room 4 |
Room 5 |
Room 6 |
Room 7 |
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10:00AM |
OP: Opening |
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10:30AM |
Break |
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10:45AM |
VT1: Krakow Virtual Tour |
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11:45AM |
Break |
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12:00PM |
R1: Differential Evolution |
R2: Genetic Algorithms - I |
R3: Evolutionary Computation for Dynamic and Uncertain Environments |
R4: Multi-objective Evolutionary Algorithms - I |
SS44: Evolutionary Algorithms for Complex Optimization in the Energy Domain |
R5: Real World Applications - I |
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1:00PM |
Break |
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1:05PM |
R6: Learning Classifier Systems |
SS2: Memetic Computing |
R7: Discrete and Combinatorial Optimization |
SS22: Bioinformatics and Bioengineering Applications |
SS4: Nature-Inspired Algorithms and Machine Learning |
R8: Real World Applications - II |
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2:15PM |
Break |
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2:30PM |
AW: Awards Ceremony |
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3:30PM |
Break |
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3:45PM |
P1: Plenary - Xin Yao (When Everything Else Fails, Try Co-evolution) |
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4:45PM |
Break |
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5:00PM |
P2: Plenary - Marco Dorigo (Towards Robust and Secure Robot Swarms) |
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6:00PM |
Break |
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6:05PM |
SBF: IEEE Student Branch Forum |
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7:05PM |
End of day |
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Wednesday, June 30th, 2021 |
| Time |
Room 1 |
Room 2 |
Room 3 |
Room 4 |
Room 5 |
Room 6 |
Room 7 |
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9:00AM |
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R9: Genetic Programming and Symbolic Regression |
SS16-I: Evolutionary Scheduling and Combinatorial Optimisation - I |
SS30: Accelerated Evolutionary Algorithms for Deep Learning and Parallel Models in Future Generation Computing |
SS1: Evolutionary Unsupervised Learning and Applications |
SS20+25: Evolutionary Computation in Healthcare |
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10:00AM |
Break |
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10:05AM |
SS3: Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction |
SS46: Special Session Associated with Numerical Optimization Competitions |
SS18: Benchmarking of Computational Intelligence Algorithms (BOCIA) |
SS9: Data-Driven Evolutionary Optimization of Computationally Expensive Problems |
SS5-I: Evolutionary Deep Learning and Applications - I |
R10: Real World Applications - III |
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11:15AM |
Break |
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11:30AM |
PD1: Panel Discussion: Evolutionary Computation in Real-World Applications |
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12:30PM |
Break |
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1:00PM |
R11: Large-scale Optimization and Data-mining |
R12: Genetic Algorithms - II |
SS57+42: Representation Learning and Automated Meta-heuristics |
R13: Multi-objective Evolutionary Algorithms - II |
R14: Evolved Neural Networks - I |
R15: Real World Applications - IV |
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2:00PM |
Break |
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2:05PM |
R16: Swarm Intelligence Algorithms - I |
R17: Heuristics, Meta-heuristics and Hyper-heuristics - I |
SS41: Candidate Solutions Representation and Fitness Landscape Manipulation |
SS33: Advances in Decomposition-based Evolutionary Multi-objective Optimization (ADEMO) |
R18: Meta-modeling and Surrogate Models |
R19: Finance and Economics |
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3:15PM |
Break |
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3:30PM |
P3: Plenary - Zbigniew Michalewicz (AI-based business applications and the EC research) |
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4:30PM |
Break |
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4:45PM |
P4: Plenary - Carlos Artemio Coello Coello (Lessons Learned after 25 Years Designing Multi-Objective Evolutionary Algorithms) |
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5:45PM |
Break |
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6:00PM |
VT2: Krakow Virtual Tour |
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7:00PM |
End of day |
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Thursday, July 1st, 2021 |
| Time |
Room 1 |
Room 2 |
Room 3 |
Room 4 |
Room 5 |
Room 6 |
Room 7 |
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9:00AM |
|
R20: Evolutionary Games and Multi-agent Systems |
SS43: Bilevel Optimization: Methods and Applications |
SS19: Evolutionary Multi-tasking |
SS37: Multimodal Multiobjective Path Planing Optimization |
SS32-I: Real-World and Industry Applications of Evolutionary Computation - I |
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10:00AM |
Break |
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10:05AM |
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R21: Genetic Algorithms - III |
SS16-II: Evolutionary Scheduling and Combinatorial Optimisation - II |
SS21: Evolutionary Many-objective Optimization: Methods and Application |
SS61: Niching Methods for Multimodal Optimization |
SS32-II: Real-World and Industry Applications of Evolutionary Computation - II |
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11:15AM |
Break |
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1:00PM |
R22: Classification, Clustering, and Data-mining |
SS13: Games |
SS16-III: Evolutionary Scheduling and Combinatorial Optimisation - III |
SS7: Large-scale Multi-/Many-objective Optimization and Its Applications |
SS5-II: Evolutionary Deep Learning and Applications - II |
R23: Biometrics, Bioinformatics and Biomedical Applications |
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2:00PM |
Break |
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2:05PM |
R24: Swarm Intelligence Algorithms - II |
R25: Heuristics, Meta-heuristics and Hyper-heuristics - II |
SS35+36: Evolutionary Computation and Learning for Software |
R26: Multi-objective Evolutionary Algorithms - III |
R27: Evolved Neural Networks - II |
R28: Parallel and Distributed Algorithms |
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3:15PM |
Break |
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3:30PM |
P5: Plenary - Roman Słowiński (Evolutionary Multiobjective Optimization with Humans in the Loop) |
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4:30PM |
Break |
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4:45PM |
P6: Plenary - Risto Miikkulainen (Neuroevolution: A Synergy of Evolution and Learning) |
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5:45PM |
Break |
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6:00PM |
PD2: Panel Discussion: Journeys to Success within in the Computational Intelligence Industry |
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7:30PM |
End of day |
